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Sample records for optical character recognition

  1. An Optical Character Recognition for Handwritten Devanagari Script

    Directory of Open Access Journals (Sweden)

    Trupti R. Zalke

    2015-01-01

    Full Text Available Optical Character Recognition is process of recognition of character from scanned document and lots of OCR now available in the market. But most of these systems work for Roman, Chinese, Japanese and Arabic characters . There are no sufficient number of work on Indian language script like Devanagari so this paper present a review on optical character recognition on handwritten Devanagari script.

  2. Rapid Feature Extraction for Optical Character Recognition

    CERN Document Server

    Hossain, M Zahid; Yan, Hong

    2012-01-01

    Feature extraction is one of the fundamental problems of character recognition. The performance of character recognition system is depends on proper feature extraction and correct classifier selection. In this article, a rapid feature extraction method is proposed and named as Celled Projection (CP) that compute the projection of each section formed through partitioning an image. The recognition performance of the proposed method is compared with other widely used feature extraction methods that are intensively studied for many different scripts in literature. The experiments have been conducted using Bangla handwritten numerals along with three different well known classifiers which demonstrate comparable results including 94.12% recognition accuracy using celled projection.

  3. A Modified Back propagation Algorithm for Optical Character Recognition

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    Jitendra Shrivastav

    2013-06-01

    Full Text Available Character Recognition (CR has been an active area of research and due to its diverse applicable environment; it continues to be a challenging research topic. There is a clear need for optical character recognition in order to provide a fast and accurate method to search both existing images as well as large archives of existing paper documents. However, existing optical character recognition programs suffer from a flawed tradeoff between speed and accuracy, making it less attractive for large quantities of documents. In this thesis, we present a new neural network based method for optical character recognition as well as handwritten character recognition. Experimental results show that our proposed method achieves highest percent accuracy in optical character recognition. We present an overview of existing handwritten character recognition techniques. All these algorithms are described more or less on their own. Handwritten character recognition is a very popular and computationally expensive task. We also explain the fundamentals of handwritten character recognition. We describe today’s approaches for handwritten character recognition. From the broad variety of efficient techniques that have been developed we will compare the most important ones. We will systematize the techniques and analyze their performance based on both their run time performance and theoretical considerations. Their strengths and weaknesses are also investigated. It turns out that the behavior of the algorithms is much more similar as to be expected.

  4. Optical character recognition systems for different languages with soft computing

    CERN Document Server

    Chaudhuri, Arindam; Badelia, Pratixa; K Ghosh, Soumya

    2017-01-01

    The book offers a comprehensive survey of soft-computing models for optical character recognition systems. The various techniques, including fuzzy and rough sets, artificial neural networks and genetic algorithms, are tested using real texts written in different languages, such as English, French, German, Latin, Hindi and Gujrati, which have been extracted by publicly available datasets. The simulation studies, which are reported in details here, show that soft-computing based modeling of OCR systems performs consistently better than traditional models. Mainly intended as state-of-the-art survey for postgraduates and researchers in pattern recognition, optical character recognition and soft computing, this book will be useful for professionals in computer vision and image processing alike, dealing with different issues related to optical character recognition.

  5. Optical character recognition of handwritten Arabic using hidden Markov models

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    Aulama, Mohannad M. [University of Jordan; Natsheh, Asem M. [University of Jordan; Abandah, Gheith A. [University of Jordan; Olama, Mohammed M [ORNL

    2011-01-01

    The problem of optical character recognition (OCR) of handwritten Arabic has not received a satisfactory solution yet. In this paper, an Arabic OCR algorithm is developed based on Hidden Markov Models (HMMs) combined with the Viterbi algorithm, which results in an improved and more robust recognition of characters at the sub-word level. Integrating the HMMs represents another step of the overall OCR trends being currently researched in the literature. The proposed approach exploits the structure of characters in the Arabic language in addition to their extracted features to achieve improved recognition rates. Useful statistical information of the Arabic language is initially extracted and then used to estimate the probabilistic parameters of the mathematical HMM. A new custom implementation of the HMM is developed in this study, where the transition matrix is built based on the collected large corpus, and the emission matrix is built based on the results obtained via the extracted character features. The recognition process is triggered using the Viterbi algorithm which employs the most probable sequence of sub-words. The model was implemented to recognize the sub-word unit of Arabic text raising the recognition rate from being linked to the worst recognition rate for any character to the overall structure of the Arabic language. Numerical results show that there is a potentially large recognition improvement by using the proposed algorithms.

  6. Optical character recognition of handwritten Arabic using hidden Markov models

    Science.gov (United States)

    Aulama, Mohannad M.; Natsheh, Asem M.; Abandah, Gheith A.; Olama, Mohammed M.

    2011-04-01

    The problem of optical character recognition (OCR) of handwritten Arabic has not received a satisfactory solution yet. In this paper, an Arabic OCR algorithm is developed based on Hidden Markov Models (HMMs) combined with the Viterbi algorithm, which results in an improved and more robust recognition of characters at the sub-word level. Integrating the HMMs represents another step of the overall OCR trends being currently researched in the literature. The proposed approach exploits the structure of characters in the Arabic language in addition to their extracted features to achieve improved recognition rates. Useful statistical information of the Arabic language is initially extracted and then used to estimate the probabilistic parameters of the mathematical HMM. A new custom implementation of the HMM is developed in this study, where the transition matrix is built based on the collected large corpus, and the emission matrix is built based on the results obtained via the extracted character features. The recognition process is triggered using the Viterbi algorithm which employs the most probable sequence of sub-words. The model was implemented to recognize the sub-word unit of Arabic text raising the recognition rate from being linked to the worst recognition rate for any character to the overall structure of the Arabic language. Numerical results show that there is a potentially large recognition improvement by using the proposed algorithms.

  7. Optical character recognition reading aid for the visually impaired.

    Science.gov (United States)

    Grandin, Juan Carlos; Cremaschi, Fabian; Lombardo, Elva; Vitu, Ed; Dujovny, Manuel

    2008-06-01

    An optical character recognition (OCR) reading machine is a significant help for visually impaired patients. An OCR reading machine is used. This instrument can provide a significant help in order to improve the quality of life of patients with low vision or blindness.

  8. Structural model constructing for optical handwritten character recognition

    Science.gov (United States)

    Khaustov, P. A.; Spitsyn, V. G.; Maksimova, E. I.

    2017-02-01

    The article is devoted to the development of the algorithms for optical handwritten character recognition based on the structural models constructing. The main advantage of these algorithms is the low requirement regarding the number of reference images. The one-pass approach to a thinning of the binary character representation has been proposed. This approach is based on the joint use of Zhang-Suen and Wu-Tsai algorithms. The effectiveness of the proposed approach is confirmed by the results of the experiments. The article includes the detailed description of the structural model constructing algorithm’s steps. The proposed algorithm has been implemented in character processing application and has been approved on MNIST handwriting characters database. Algorithms that could be used in case of limited reference images number were used for the comparison.

  9. Optical Character Recognition for printed Tamil text using Unicode

    Institute of Scientific and Technical Information of China (English)

    SEETHALAKSHMI R.; SREERANJANI T.R.; BALACHANDAR T.; Abnikant Singh; Markandey Singh; Ritwaj Ratan; Sarvesh Kumar

    2005-01-01

    Optical Character Recognition (OCR) refers to the process of converting printed Tamil text documents into software translated Unicode Tamil Text. The printed documents available in the form of books, papers, magazines, etc. are scanned using standard scanners which produce an image of the scanned document. As part of the preprocessing phase the image file is checked for skewing. Ifthe image is skewed, it is corrected by a simple rotation technique in the appropriate direction. Then the image is passed through a noise elimination phase and is binarized. The preprocessed image is segmented using an algorithm which decomposes the scanned text into paragraphs using special space detection technique and then the paragraphs into lines using vertical histograms, and lines into words using horizontal histograms, and words into character image glyphs using horizontal histograms.Each image glyph is comprised of 32x32 pixels. Thus a database of character image glyphs is created out of the segmentation phase. Then all the image glyphs are considered for recognition using Unicode mapping. Each image glyph is passed through various routines which extract the features of the glyph. The various features that are considered for classification are the character height, character width, the number of horizontal lines (long and short), the number of vertical lines (long and short), the horizontally oriented curves, the vertically oriented curves, the number of circles, number of slope lines, image centroid and special dots. The glyphs are now set ready for classification based on these features. The extracted features are passed to a Support Vector Machine (SVM) where the characters are classified by Supervised Learning Algorithm. These classes are mapped onto Unicode for recognition. Then the text is reconstructed using Unicode fonts.

  10. Character Recognition (Devanagari Script

    Directory of Open Access Journals (Sweden)

    Ankita Karia

    2015-04-01

    Full Text Available Character Recognition is has found major interest in field of research and practical application to analyze and study characters in different languages using image as their input. In this paper the user writes the Devanagari character using mouse as a plotter and then the corresponding character is saved in the form of image. This image is processed using Optical Character Recognition in which location, segmentation, pre-processing of image is done. Later Neural Networks is used to identify all the characters by the further process of OCR i.e. by using feature extraction and post-processing of image. This entire process is done using MATLAB.

  11. Using K-Nearest Neighbor in Optical Character Recognition

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    Veronica Ong

    2016-03-01

    Full Text Available The growth in computer vision technology has aided society with various kinds of tasks. One of these tasks is the ability of recognizing text contained in an image, or usually referred to as Optical Character Recognition (OCR. There are many kinds of algorithms that can be implemented into an OCR. The K-Nearest Neighbor is one such algorithm. This research aims to find out the process behind the OCR mechanism by using K-Nearest Neighbor algorithm; one of the most influential machine learning algorithms. It also aims to find out how precise the algorithm is in an OCR program. To do that, a simple OCR program to classify alphabets of capital letters is made to produce and compare real results. The result of this research yielded a maximum of 76.9% accuracy with 200 training samples per alphabet. A set of reasons are also given as to why the program is able to reach said level of accuracy.

  12. Low-Budget, Cost-Effective OCR: Optical Character Recognition for MS-DOS Micros.

    Science.gov (United States)

    Perez, Ernest

    1990-01-01

    Discusses optical character recognition (OCR) for use with MS-DOS microcomputers. Cost effectiveness is considered, three types of software approaches to character recognition are explained, hardware and operation requirements are described, possible library applications are discussed, future OCR developments are suggested, and a list of OCR…

  13. The Optical Character Recognition for Cursive Script Using HMM: A Review

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    Saeeda Naz

    2014-11-01

    Full Text Available Automatic Character Recognition has wide variety of applications such as automatic postal mail sorting, number plate recognition and automatic form of reader and entering text from PDA's etc. Cursive script’s Automatic Character Recognition is a complex process facing unique issues unlike other scripts. Many solutions have been proposed in the literature to solve complexities of cursive scripts character recognition. This paper present a comprehensive literature review of the Optical Character Recognition (OCR for off-line and on-line character recognition for Urdu, Arabic and Persian languages, based on Hidden Markov Model (HMM. We surveyed all most all significant approaches proposed and concluded future directions of OCR for cursive languages.

  14. Design of an Optical Character Recognition System for Camera-based Handheld Devices

    CERN Document Server

    Mollah, Ayatullah Faruk; Basu, Subhadip; Nasipuri, Mita

    2011-01-01

    This paper presents a complete Optical Character Recognition (OCR) system for camera captured image/graphics embedded textual documents for handheld devices. At first, text regions are extracted and skew corrected. Then, these regions are binarized and segmented into lines and characters. Characters are passed into the recognition module. Experimenting with a set of 100 business card images, captured by cell phone camera, we have achieved a maximum recognition accuracy of 92.74%. Compared to Tesseract, an open source desktop-based powerful OCR engine, present recognition accuracy is worth contributing. Moreover, the developed technique is computationally efficient and consumes low memory so as to be applicable on handheld devices.

  15. GENETIC ALGORITHM AND NEURAL NETWORK FOR OPTICAL CHARACTER RECOGNITION

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    Hendy Yeremia

    2013-01-01

    Full Text Available Computer system has been able to recognize writing as human brain does. The method mostly used for character recognition is the backpropagation network. Backpropagation network has been known for its accuracy because it allows itself to learn and improving itself thus it can achieve higher accuracy. On the other hand, backpropagation was less to be used because of its time length needed to train the network to achieve the best result possible. In this study, backpropagation network algorithm is combined with genetic algorithm to achieve both accuracy and training swiftness for recognizing alphabets. Genetic algorithm is used to define the best initial values for the network’s architecture and synapses’ weight thus within a shorter period of time, the network could achieve the best accuracy. The optimized backpropagation network has better accuracy and less training time than the standard backpropagation network. The accuracy in recognizing character differ by 10, 77%, with a success rate of 90, 77% for the optimized backpropagation and 80% accuracy for the standard backpropagation network. The training time needed for backpropagation learning phase improved significantly from 03 h, 14 min and 40 sec, a standard backpropagation training time, to 02 h 18 min and 1 sec for the optimized backpropagation network.

  16. An Overview of Optical Character Recognition (OCR) Technology and Techniques.

    Science.gov (United States)

    1978-06-01

    using optico -electric filters. In practice, the choice of preprocessing techniques must necessarily be related to the recognition method. For example...inter- face), Recognition Unit and Operator Communication device. A brief description of each major system component including the Input Sensor follows...accomplish several types of mark- sensor recognition. Together, they are ’ capable of recognizing machine and handprinted data intermixed on the same line. .3

  17. Design of an Optical Character Recognition System for Camera-based Handheld Devices

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    Ayatullah Faruk Mollah

    2011-07-01

    Full Text Available This paper presents a complete Optical Character Recognition (OCR system for camera captured image/graphics embedded textual documents for handheld devices. At first, text regions are extracted and skew corrected. Then, these regions are binarized and segmented into lines and characters. Characters are passed into the recognition module. Experimenting with a set of 100 business card images, captured by cell phone camera, we have achieved a maximum recognition accuracy of 92.74%. Compared to Tesseract, an open source desktop-based powerful OCR engine, present recognition accuracy is worth contributing. Moreover, the developed technique is computationally efficient and consumes low memory so as to be applicable on handheld devices.

  18. Long-range optical character recognition for product ID

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    Banta, Larry E.; Pertl, Franz A.; Rosenberry-Friend, Kimberly A.

    1998-10-01

    An automated product tag reading system based on CCD cameras and computer image processing has been developed by West Virginia University and demonstrated at the Weirton Steel Corporation. The system reads both a 50-mil barcode and a string of six numbers on a four-inch by six-inch tag fastened to the end of a steel slab. Feedback from the image is used to point and zoom the camera, making the system effective at ranges up to thirty feet, and in bright sunlight-situations where handheld barcode scanners are ineffective. A video camera is mounted on a pan/tilt head and connected to a personal computer through a frame grabber board. The whole system is mounted on a slab hauler--a huge wheeled machine for carrying 100 tons of steel slabs at a time. The slab hauler backs into position and presses `start' on a touchscreen operator interface. A wide-angle image is grabbed, and the computer analyzes the images to find product ID tags in scene. The camera is then zoomed and pointed one-by-one at the tags for closeup images. Geometric warping is done on the closeup images to correct for viewing angle distortion, and both the barcode and the alphanumeric code are read by the software and reported to the inventory management system via radio modern. This paper discusses the neural network-based system for reading the characters on the tag. The camera pointing system and barcode reader are discussed in a companion paper.

  19. Development of an optical character recognition pipeline for handwritten form fields from an electronic health record.

    Science.gov (United States)

    Rasmussen, Luke V; Peissig, Peggy L; McCarty, Catherine A; Starren, Justin

    2012-06-01

    Although the penetration of electronic health records is increasing rapidly, much of the historical medical record is only available in handwritten notes and forms, which require labor-intensive, human chart abstraction for some clinical research. The few previous studies on automated extraction of data from these handwritten notes have focused on monolithic, custom-developed recognition systems or third-party systems that require proprietary forms. We present an optical character recognition processing pipeline, which leverages the capabilities of existing third-party optical character recognition engines, and provides the flexibility offered by a modular custom-developed system. The system was configured and run on a selected set of form fields extracted from a corpus of handwritten ophthalmology forms. The processing pipeline allowed multiple configurations to be run, with the optimal configuration consisting of the Nuance and LEADTOOLS engines running in parallel with a positive predictive value of 94.6% and a sensitivity of 13.5%. While limitations exist, preliminary experience from this project yielded insights on the generalizability and applicability of integrating multiple, inexpensive general-purpose third-party optical character recognition engines in a modular pipeline.

  20. Optical character recognition of camera-captured images based on phase features

    Science.gov (United States)

    Diaz-Escobar, Julia; Kober, Vitaly

    2015-09-01

    Nowadays most of digital information is obtained using mobile devices specially smartphones. In particular, it brings the opportunity for optical character recognition in camera-captured images. For this reason many recognition applications have been recently developed such as recognition of license plates, business cards, receipts and street signal; document classification, augmented reality, language translator and so on. Camera-captured images are usually affected by geometric distortions, nonuniform illumination, shadow, noise, which make difficult the recognition task with existing systems. It is well known that the Fourier phase contains a lot of important information regardless of the Fourier magnitude. So, in this work we propose a phase-based recognition system exploiting phase-congruency features for illumination/scale invariance. The performance of the proposed system is tested in terms of miss classifications and false alarms with the help of computer simulation.

  1. Optical Character Recognition Based Speech Synthesis System Using LabVIEW

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    S.K. Singla

    2014-10-01

    Full Text Available Knowledge extraction by just listening to sounds is a distinctive property. Speech signal is more effective means of communication than text because blind and visually impaired persons can also respond to sounds. This paper aims to develop a cost effective, and user friendly optical character recognition (OCR based speech synthesis system. The OCR based speech synthesis system has been developed using Laboratory virtual instruments engineering workbench (LabVIEW 7.1.

  2. Optical Character Recognition for Isolated Offline Handwritten Devanagari Numerals Using Wavelets

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    Gaurav Y. Tawde

    2014-02-01

    Full Text Available This paper presents a method of recognition of isolated offline handwritten Devanagari numerals using wavelets and neural network classifier. This method of optical character recognition takes the handwritten numeral image as input. After pre-processing, it is subjected to single level wavelet decomposition using Daubechies-4 wavelet filter. This wavelet decomposition allows viewing the input numeral at multiple resolutions. The Low-Low band components are used as inputs to multilayer perceptron (MLP classifier. The feed forward back propagation algorithm is used for classification of the input numeral.

  3. A method of neighbor classes based SVM classification for optical printed Chinese character recognition.

    Science.gov (United States)

    Zhang, Jie; Wu, Xiaohong; Yu, Yanmei; Luo, Daisheng

    2013-01-01

    In optical printed Chinese character recognition (OPCCR), many classifiers have been proposed for the recognition. Among the classifiers, support vector machine (SVM) might be the best classifier. However, SVM is a classifier for two classes. When it is used for multi-classes in OPCCR, its computation is time-consuming. Thus, we propose a neighbor classes based SVM (NC-SVM) to reduce the computation consumption of SVM. Experiments of NC-SVM classification for OPCCR have been done. The results of the experiments have shown that the NC-SVM we proposed can effectively reduce the computation time in OPCCR.

  4. A method of neighbor classes based SVM classification for optical printed Chinese character recognition.

    Directory of Open Access Journals (Sweden)

    Jie Zhang

    Full Text Available In optical printed Chinese character recognition (OPCCR, many classifiers have been proposed for the recognition. Among the classifiers, support vector machine (SVM might be the best classifier. However, SVM is a classifier for two classes. When it is used for multi-classes in OPCCR, its computation is time-consuming. Thus, we propose a neighbor classes based SVM (NC-SVM to reduce the computation consumption of SVM. Experiments of NC-SVM classification for OPCCR have been done. The results of the experiments have shown that the NC-SVM we proposed can effectively reduce the computation time in OPCCR.

  5. A simple and efficient optical character recognition system for basic symbols in printed Kannada text

    Indian Academy of Sciences (India)

    R Sanjeev Kunte; R D Sudhaker Samuel

    2007-10-01

    Optical Character Recognition (OCR) systems have been effectively developed for the recognition of printed characters of non-Indian languages. Efforts are on the way for the development of efficient OCR systems for Indian languages, especially for Kannada, a popular South Indian language. We present in this paper an OCR system developed for the recognition of basic characters (vowels and consonants) in printed Kannada text, which can handle different font sizes and font types. Hu’s invariant moments and Zernike moments that have been progressively used in pattern recognition are used in our system to extract the features of printed Kannada characters. Neural classifiers have been effectively used for the classification of characters based on moment features. An encouraging recognition rate of 96·8% has been obtained. The system methodology can be extended for the recognition of other south Indian languages, especially for Telugu.

  6. Optical Character Recognition Applied to Romanian Printed Texts of the 18th–20th Century

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    Svetlana Cojocaru

    2016-04-01

    Full Text Available The paper discusses Optical Character Recognition (OCR of historical texts of the 18th–20th century in the Romanian language using the Cyrillic script. We differ three epochs (approximately, the 18th, 19th, and 20th centuries, with different usage of the Cyrillic alphabet in Romanian and, correspondingly, different approach to OCR. We developed historical alphabets and sets of glyphs recognition templates specific for each epoch. The dictionaries in proper alphabets and orthographies were also created. In addition, virtual keyboards, fonts, transliteration utilities, etc. were developed. The resulting technology and toolset permit successful recognition of historical Romanian texts in the Cyrillic script. After transliteration to the modern Latin script we obtain no-barrier access to historical documents.

  7. A survey on optical character recognition for Bangla and Devanagari scripts

    Indian Academy of Sciences (India)

    Soumen Bag; Gaurav Harit

    2013-02-01

    The past few decades have witnessed an intensive research on optical character recognition (OCR) for Roman, Chinese, and Japanese scripts. A lot of work has been also reported on OCR efforts for various Indian scripts, like Devanagari, Bangla, Oriya, Tamil, Telugu, Malayalam, Kannada, Gurmukhi, Gujarati, etc. In this paper, we present a review of OCR work on Indian scripts, mainly on Bangla and Devanagari—the two most popular scripts in India. We have summarized most of the published papers on this topic and have also analysed the various methodologies and their reported results. Future directions of research in OCR for Indian scripts have been also given.

  8. APPLYING PRINCIPAL COMPONENT ANALYSIS, MULTILAYER PERCEPTRON AND SELF-ORGANIZING MAPS FOR OPTICAL CHARACTER RECOGNITION

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    Khuat Thanh Tung

    2016-11-01

    Full Text Available Optical Character Recognition plays an important role in data storage and data mining when the number of documents stored as images is increasing. It is expected to find the ways to convert images of typewritten or printed text into machine-encoded text effectively in order to support for the process of information handling effectively. In this paper, therefore, the techniques which are being used to convert image into editable text in the computer such as principal component analysis, multilayer perceptron network, self-organizing maps, and improved multilayer neural network using principal component analysis are experimented. The obtained results indicated the effectiveness and feasibility of the proposed methods.

  9. Classification of remotely sensed data using OCR-inspired neural network techniques. [Optical Character Recognition

    Science.gov (United States)

    Kiang, Richard K.

    1992-01-01

    Neural networks have been applied to classifications of remotely sensed data with some success. To improve the performance of this approach, an examination was made of how neural networks are applied to the optical character recognition (OCR) of handwritten digits and letters. A three-layer, feedforward network, along with techniques adopted from OCR, was used to classify Landsat-4 Thematic Mapper data. Good results were obtained. To overcome the difficulties that are characteristic of remote sensing applications and to attain significant improvements in classification accuracy, a special network architecture may be required.

  10. Novel Ontologies-based Optical Character Recognition-error Correction Cooperating with Graph Component Extraction

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    Sarunya Kanjanawattana

    2017-01-01

    Full Text Available literature. Extracting graph information clearly contributes to readers, who are interested in graph information interpretation, because we can obtain significant information presenting in the graph. A typical tool used to transform image-based characters to computer editable characters is optical character recognition (OCR. Unfortunately, OCR cannot guarantee perfect results, because it is sensitive to noise and input quality. This becomes a serious problem because misrecognition provides misunderstanding information to readers and causes misleading communication. In this study, we present a novel method for OCR-error correction based on bar graphs using semantics, such as ontologies and dependency parsing. Moreover, we used a graph component extraction proposed in our previous study to omit irrelevant parts from graph components. It was applied to clean and prepare input data for this OCR-error correction. The main objectives of this paper are to extract significant information from the graph using OCR and to correct OCR errors using semantics. As a result, our method provided remarkable performance with the highest accuracies and F-measures. Moreover, we examined that our input data contained less of noise because of an efficiency of our graph component extraction. Based on the evidence, we conclude that our solution to the OCR problem achieves the objectives.

  11. Shift- and deformation-robust optical character recognition based on parallel extraction of simple features

    Science.gov (United States)

    Jang, Ju-Seog; Shin, Dong-Hak

    1997-03-01

    For a flexible pattern recognition system that is robust to the input variations, a feature extraction approach is investigated. Two types of features are extracted: one is line orientations, and the other is the eigenvectors of the covariance matrix of the patterns that cannot be distinguished with the line orientation features alone. For the feature extraction, the Vander Lugt-type filters are used, which are recorded in a small spot of holographic recording medium by use of multiplexing techniques. A multilayer perceptron implemented in a computer is trained with a set of optically extracted features, so that it can recognize the input patterns that are not used in the training. Through preliminary experiments, where English character patterns composed of only straight line segments were tested, the feasibility of our approach is demonstrated.

  12. Aplikasi Penerjemah Bahasa Inggris – Indonesia dengan Optical Character Recognition Berbasis Android

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    Anisa Eka Utami

    2016-01-01

    Full Text Available Perangkat lunak untuk pengenalan karakter yang terdapat dalam ponsel pintar khususnya berbasis Android dikembangkan dengan penekanan pada mobilitas, portabilitas, ruang penyimpanan, perangkat keras, dan keterbatasan jangkauan dapat dipecahkan. Akan tetapi, kinerja sebuah ponsel pintar berbasis Android dan komputer berbeda maka kecepatan pengenalan karakter juga akan berpengaruh. Masalah ini tampaknya akan menunjukkan suatu solusi, yaitu dengan salah satu inovasi yang diterapkankan ke dalam perangkat Android dengan teknologi OCR (Optical Character Recognition. Perencanaan sistem menggunakan pengembangan perangkat lunak berorientasi pemakaian ulang karena menggunakan komponen yang dapat dipakai ulang dalam pengembangannya. Sistem ini dibuat dengan memanfaatkan engine Tesseract OCR yang dikembangkan oleh Google bersifat open source. Perangkat lunak yang digunakan untuk merancang layout dan implementasi sistem, yaitu menggunakan lingkungan pengembang Android Studio yang ditulis dengan bahasa pemrograman Java dan XML. Pengujian aplikasi penerjemah dengan OCR ini menggunakan metode white box dan menghitung akurasi pendeteksian karakter. Hasil perhitungan presentase akurasi deteksi karakter yang diberikan aplikasi terhadap keseluruhan sampel yang diuji mencapai 97,5%.

  13. Printed Text Character Analysis Version-II: Optimized optical character recognition for noisy images with the new user training and background detection mechanism

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    Satyaki Roy

    2014-06-01

    Full Text Available The proposed system performs the task of analysing snapshots of written text and creating fully customizable text files using Optical Character Recognition (OCR technology. It is known that new font styles and writing formats are introduced everyday but the existing systems find it increasingly difficult to incorporate the newly emerging font styles. The authors have already proposed a system which gives the user complete liberty to effortlessly train the system to handle new fonts using the character dictionary and user training mechanism. The present version makes the process of character recognition more accurate and effective by introducing optimization in the recognition process, a mechanism to handle noisy text images and also a background detection mechanism to differentiate the written symbol from the image background.

  14. The use of Optical Character Recognition (OCR in the digitisation of herbarium specimen labels

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    Robyn Drinkwater

    2014-05-01

    Full Text Available At the Royal Botanic Garden Edinburgh (RBGE the use of Optical Character Recognition (OCR to aid the digitisation process has been investigated. This was tested using a herbarium specimen digitisation process with two stages of data entry. Records were initially batch-processed to add data extracted from the OCR text prior to being sorted based on Collector and/or Country. Using images of the specimens, a team of six digitisers then added data to the specimen records. To investigate whether the data from OCR aid the digitisation process, they completed a series of trials which compared the efficiency of data entry between sorted and unsorted batches of specimens. A survey was carried out to explore the opinion of the digitisation staff to the different sorting options. In total 7,200 specimens were processed.When compared to an unsorted, random set of specimens, those which were sorted based on data added from the OCR were quicker to digitise. Of the methods tested here, the most successful in terms of efficiency used a protocol which required entering data into a limited set of fields and where the records were filtered by Collector and Country. The survey and subsequent discussions with the digitisation staff highlighted their preference for working with sorted specimens, in which label layout, locations and handwriting are likely to be similar, and so a familiarity with the Collector or Country is rapidly established.

  15. The use of Optical Character Recognition (OCR) in the digitisation of herbarium specimen labels.

    Science.gov (United States)

    Drinkwater, Robyn E; Cubey, Robert W N; Haston, Elspeth M

    2014-01-01

    At the Royal Botanic Garden Edinburgh (RBGE) the use of Optical Character Recognition (OCR) to aid the digitisation process has been investigated. This was tested using a herbarium specimen digitisation process with two stages of data entry. Records were initially batch-processed to add data extracted from the OCR text prior to being sorted based on Collector and/or Country. Using images of the specimens, a team of six digitisers then added data to the specimen records. To investigate whether the data from OCR aid the digitisation process, they completed a series of trials which compared the efficiency of data entry between sorted and unsorted batches of specimens. A survey was carried out to explore the opinion of the digitisation staff to the different sorting options. In total 7,200 specimens were processed. When compared to an unsorted, random set of specimens, those which were sorted based on data added from the OCR were quicker to digitise. Of the methods tested here, the most successful in terms of efficiency used a protocol which required entering data into a limited set of fields and where the records were filtered by Collector and Country. The survey and subsequent discussions with the digitisation staff highlighted their preference for working with sorted specimens, in which label layout, locations and handwriting are likely to be similar, and so a familiarity with the Collector or Country is rapidly established.

  16. Synthesis of Common Arabic Handwritings to Aid Optical Character Recognition Research

    Directory of Open Access Journals (Sweden)

    Laslo Dinges

    2016-03-01

    Full Text Available Document analysis tasks such as pattern recognition, word spotting or segmentation, require comprehensive databases for training and validation. Not only variations in writing style but also the used list of words is of importance in the case that training samples should reflect the input of a specific area of application. However, generation of training samples is expensive in the sense of manpower and time, particularly if complete text pages including complex ground truth are required. This is why there is a lack of such databases, especially for Arabic, the second most popular language. However, Arabic handwriting recognition involves different preprocessing, segmentation and recognition methods. Each requires particular ground truth or samples to enable optimal training and validation, which are often not covered by the currently available databases. To overcome this issue, we propose a system that synthesizes Arabic handwritten words and text pages and generates corresponding detailed ground truth. We use these syntheses to validate a new, segmentation based system that recognizes handwritten Arabic words. We found that a modification of an Active Shape Model based character classifiers—that we proposed earlier—improves the word recognition accuracy. Further improvements are achieved, by using a vocabulary of the 50,000 most common Arabic words for error correction.

  17. Synthesis of Common Arabic Handwritings to Aid Optical Character Recognition Research.

    Science.gov (United States)

    Dinges, Laslo; Al-Hamadi, Ayoub; Elzobi, Moftah; El-Etriby, Sherif

    2016-03-11

    Document analysis tasks such as pattern recognition, word spotting or segmentation, require comprehensive databases for training and validation. Not only variations in writing style but also the used list of words is of importance in the case that training samples should reflect the input of a specific area of application. However, generation of training samples is expensive in the sense of manpower and time, particularly if complete text pages including complex ground truth are required. This is why there is a lack of such databases, especially for Arabic, the second most popular language. However, Arabic handwriting recognition involves different preprocessing, segmentation and recognition methods. Each requires particular ground truth or samples to enable optimal training and validation, which are often not covered by the currently available databases. To overcome this issue, we propose a system that synthesizes Arabic handwritten words and text pages and generates corresponding detailed ground truth. We use these syntheses to validate a new, segmentation based system that recognizes handwritten Arabic words. We found that a modification of an Active Shape Model based character classifiers-that we proposed earlier-improves the word recognition accuracy. Further improvements are achieved, by using a vocabulary of the 50,000 most common Arabic words for error correction.

  18. Kannada Character Recognition System A Review

    CERN Document Server

    Indira, K

    2010-01-01

    Intensive research has been done on optical character recognition ocr and a large number of articles have been published on this topic during the last few decades. Many commercial OCR systems are now available in the market, but most of these systems work for Roman, Chinese, Japanese and Arabic characters. There are no sufficient number of works on Indian language character recognition especially Kannada script among 12 major scripts in India. This paper presents a review of existing work on printed Kannada script and their results. The characteristics of Kannada script and Kannada Character Recognition System kcr are discussed in detail. Finally fusion at the classifier level is proposed to increase the recognition accuracy.

  19. CHARACTER RECOGNITION OF VIDEO SUBTITLES\\

    Directory of Open Access Journals (Sweden)

    Satish S Hiremath

    2016-11-01

    Full Text Available An important task in content based video indexing is to extract text information from videos. The challenges involved in text extraction and recognition are variation of illumination on each video frame with text, the text present on the complex background and different font size of the text. Using various image processing algorithms like morphological operations, blob detection and histogram of oriented gradients the character recognition of video subtitles is implemented. Segmentation, feature extraction and classification are the major steps of character recognition. Several experimental results are shown to demonstrate the performance of the proposed algorithm

  20. A New Database of Digits Extracted from Coins with Hard-to-Segment Foreground for Optical Character Recognition Evaluation

    Directory of Open Access Journals (Sweden)

    Xingyu Pan

    2017-05-01

    Full Text Available Since the release date struck on a coin is important information of its monetary type, recognition of extracted digits may assist in identification of monetary types. However, digit images extracted from coins are challenging for conventional optical character recognition methods because the foreground of such digits has very often the same color as their background. In addition, other noises, including the wear of coin metal, make it more difficult to obtain a correct segmentation of the character shape. To address those challenges, this article presents the CoinNUMS database for automatic digit recognition. The database CoinNUMS, containing 3,006 digit images, is divided into three subsets. The first subset CoinNUMS_geni consists of 606 digit images manually cropped from high-resolution photographs of well-conserved coins from GENI coin photographs; the second subset CoinNUMS_pcgs_a consists of 1,200 digit images automatically extracted from a subset of the USA_Grading numismatic database containing coins in different quality; the last subset CoinNUMS_pcgs_m consists of 1,200 digit images manually extracted from the same coin photographs as CoinNUMS_pcgs_a. In CoinNUMS_pcgs_a and CoinNUMS_pcgs_m, the digit images are extracted from the release date. In CoinNUMS_geni, the digit images can come from the cropped date, the face value, or any other legends containing digits in the coin. To show the difficulty of these databases, we have tested recognition algorithms of the literature. The database and the results of the tested algorithms will be freely available on a dedicated website.1

  1. Quantitative computed tomography (QCT) as a radiology reporting tool by using optical character recognition (OCR) and macro program.

    Science.gov (United States)

    Lee, Young Han; Song, Ho-Taek; Suh, Jin-Suck

    2012-12-01

    The objectives are (1) to introduce a new concept of making a quantitative computed tomography (QCT) reporting system by using optical character recognition (OCR) and macro program and (2) to illustrate the practical usages of the QCT reporting system in radiology reading environment. This reporting system was created as a development tool by using an open-source OCR software and an open-source macro program. The main module was designed for OCR to report QCT images in radiology reading process. The principal processes are as follows: (1) to save a QCT report as a graphic file, (2) to recognize the characters from an image as a text, (3) to extract the T scores from the text, (4) to perform error correction, (5) to reformat the values into QCT radiology reporting template, and (6) to paste the reports into the electronic medical record (EMR) or picture archiving and communicating system (PACS). The accuracy test of OCR was performed on randomly selected QCTs. QCT as a radiology reporting tool successfully acted as OCR of QCT. The diagnosis of normal, osteopenia, or osteoporosis is also determined. Error correction of OCR is done with AutoHotkey-coded module. The results of T scores of femoral neck and lumbar vertebrae had an accuracy of 100 and 95.4 %, respectively. A convenient QCT reporting system could be established by utilizing open-source OCR software and open-source macro program. This method can be easily adapted for other QCT applications and PACS/EMR.

  2. The Impact of a Modified Repeated-Reading Strategy Paired with Optical Character Recognition on the Reading Rates of Students with Visual Impairments

    Science.gov (United States)

    Pattillo, Suzan Trefry; Heller, Kathryn Wolf; Smith, Maureen

    2004-01-01

    The repeated-reading strategy and optical character recognition were paired to demonstrate a functional relationship between the combined strategies and two factors: the reading rates of students with visual impairments and the students' self-perceptions, or attitudes, toward reading. The results indicated that all five students increased their…

  3. Offline arabic character recognition system

    Institute of Scientific and Technical Information of China (English)

    2003-01-01

    Several languages use the Arabic alphabets and arabic scripts present challenges because the letter shape is context sensitive. For the past three decades, there has been a mounting interest among researchers in this problem. In this paper we present an Arabic Character Recognition system and quence steps of recognizing Arabic text. These steps are separately discussed, and previous research work on each step is reviewed. Also in this paper we give some samples of Arabic fonts.

  4. Text vectorization based on character recognition and character stroke modeling

    Science.gov (United States)

    Fan, Zhigang; Zhou, Bingfeng; Tse, Francis; Mu, Yadong; He, Tao

    2014-03-01

    In this paper, a text vectorization method is proposed using OCR (Optical Character Recognition) and character stroke modeling. This is based on the observation that for a particular character, its font glyphs may have different shapes, but often share same stroke structures. Like many other methods, the proposed algorithm contains two procedures, dominant point determination and data fitting. The first one partitions the outlines into segments and second one fits a curve to each segment. In the proposed method, the dominant points are classified as "major" (specifying stroke structures) and "minor" (specifying serif shapes). A set of rules (parameters) are determined offline specifying for each character the number of major and minor dominant points and for each dominant point the detection and fitting parameters (projection directions, boundary conditions and smoothness). For minor points, multiple sets of parameters could be used for different fonts. During operation, OCR is performed and the parameters associated with the recognized character are selected. Both major and minor dominant points are detected as a maximization process as specified by the parameter set. For minor points, an additional step could be performed to test the competing hypothesis and detect degenerated cases.

  5. Kannada character recognition system using neural network

    Science.gov (United States)

    Kumar, Suresh D. S.; Kamalapuram, Srinivasa K.; Kumar, Ajay B. R.

    2013-03-01

    Handwriting recognition has been one of the active and challenging research areas in the field of pattern recognition. It has numerous applications which include, reading aid for blind, bank cheques and conversion of any hand written document into structural text form. As there is no sufficient number of works on Indian language character recognition especially Kannada script among 15 major scripts in India. In this paper an attempt is made to recognize handwritten Kannada characters using Feed Forward neural networks. A handwritten Kannada character is resized into 20x30 Pixel. The resized character is used for training the neural network. Once the training process is completed the same character is given as input to the neural network with different set of neurons in hidden layer and their recognition accuracy rate for different Kannada characters has been calculated and compared. The results show that the proposed system yields good recognition accuracy rates comparable to that of other handwritten character recognition systems.

  6. Radiation Dose-Rate Extraction from the Camera Image of Quince 2 Robot System using Optical Character Recognition

    Energy Technology Data Exchange (ETDEWEB)

    Cho, Jai Wan; Jeong, Kyung Min [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

    2012-05-15

    In the case of the Japanese Quince 2 robot system, 7 CCD/CMOS cameras were used. 2 CCD cameras of Quince robot are used for the forward and backward monitoring of the surroundings during navigation. And 2 CCD (or CMOS) cameras are used for monitoring the status of front-end and back-end motion mechanics such as flippers and crawlers. A CCD camera with wide field of view optics is used for monitoring the status of the communication (VDSL) cable reel. And another 2 CCD cameras are assigned for reading the indication value of the radiation dosimeter and the instrument. The Quince 2 robot measured radiation in the unit 2 reactor building refueling floor of the Fukushima nuclear power plant. The CCD camera with wide field-of-view (fisheye) lens reads indicator of the dosimeter loaded on the Quince 2 robot, which was sent to carry out investigating the unit 2 reactor building refueling floor situation. The camera image with gamma ray dose-rate information is transmitted to the remote control site via VDSL communication line. At the remote control site, the radiation information in the unit 2 reactor building refueling floor can be perceived by monitoring the camera image. To make up the radiation profile in the surveyed refueling floor, the gamma ray dose-rate information in the image should be converted to numerical value. In this paper, we extract the gamma ray dose-rate value in the unit 2 reactor building refueling floor using optical character recognition method

  7. Rapid Naming Speed and Chinese Character Recognition

    Science.gov (United States)

    Liao, Chen-Huei; Georgiou, George K.; Parrila, Rauno

    2008-01-01

    We examined the relationship between rapid naming speed (RAN) and Chinese character recognition accuracy and fluency. Sixty-three grade 2 and 54 grade 4 Taiwanese children were administered four RAN tasks (colors, digits, Zhu-Yin-Fu-Hao, characters), and two character recognition tasks. RAN tasks accounted for more reading variance in grade 4 than…

  8. Invention and validation of an automated camera system that uses optical character recognition to identify patient name mislabeled samples.

    Science.gov (United States)

    Hawker, Charles D; McCarthy, William; Cleveland, David; Messinger, Bonnie L

    2014-03-01

    Mislabeled samples are a serious problem in most clinical laboratories. Published error rates range from 0.39/1000 to as high as 1.12%. Standardization of bar codes and label formats has not yet achieved the needed improvement. The mislabel rate in our laboratory, although low compared with published rates, prompted us to seek a solution to achieve zero errors. To reduce or eliminate our mislabeled samples, we invented an automated device using 4 cameras to photograph the outside of a sample tube. The system uses optical character recognition (OCR) to look for discrepancies between the patient name in our laboratory information system (LIS) vs the patient name on the customer label. All discrepancies detected by the system's software then require human inspection. The system was installed on our automated track and validated with production samples. We obtained 1 009 830 images during the validation period, and every image was reviewed. OCR passed approximately 75% of the samples, and no mislabeled samples were passed. The 25% failed by the system included 121 samples actually mislabeled by patient name and 148 samples with spelling discrepancies between the patient name on the customer label and the patient name in our LIS. Only 71 of the 121 mislabeled samples detected by OCR were found through our normal quality assurance process. We have invented an automated camera system that uses OCR technology to identify potential mislabeled samples. We have validated this system using samples transported on our automated track. Full implementation of this technology offers the possibility of zero mislabeled samples in the preanalytic stage.

  9. Structural recognition of ancient Chinese ideographic characters

    Institute of Scientific and Technical Information of China (English)

    Li Ning; Chen Dan

    2014-01-01

    Ancient Chinese characters, typically the ideographic characters on bones and bronze before Shang Dynasty (16th—11th century B.C.), are valuable culture legacy of history. However the recognition of Ancient Chinese characters has been the task of paleography experts for long. With the help of modern computer technique, everyone can expect to be able to recognize the characters and understand the ancient inscriptions. This research is aimed to help people recognize and understand those ancient Chinese characters by combining Chinese paleography theory and computer information processing technology. Based on the analysis of ancient character features, a method for structural character recognition is proposed. The important characteristics of strokes and basic components or radicals used in recognition are introduced in detail. A system was implemented based on above method to show the effectiveness of the method.

  10. Data set for Tifinagh handwriting character recognition

    Directory of Open Access Journals (Sweden)

    Omar Bencharef

    2015-09-01

    Full Text Available The Tifinagh alphabet-IRCAM is the official alphabet of the Amazigh language widely used in North Africa [1]. It includes thirty-one basic letter and two letters each composed of a base letter followed by the sign of labialization. Normalized only in 2003 (Unicode [2], ICRAM-Tifinagh is a young character repertoire. Which needs more work on all levels. In this context we propose a data set for handwritten Tifinagh characters composed of 1376 image; 43 Image For Each character. The dataset can be used to train a Tifinagh character recognition system, or to extract the meaning characteristics of each character.

  11. System and method for character recognition

    Science.gov (United States)

    Hong, J. P. (Inventor)

    1974-01-01

    A character recognition system is disclosed in which each character in a retina, defining a scanning raster, is scanned with random lines uniformly distributed over the retina. For each type of character to be recognized the system stores a probability density function (PDF) of the random line intersection lengths and/or a PDF of the random line number of intersections. As an unknown character is scanned, the random line intersection lengths and/or the random line number of intersections are accumulated and based on a comparison with the prestored PDFs a classification of the unknown character is performed.

  12. Data set for Tifinagh handwriting character recognition.

    Science.gov (United States)

    Bencharef, Omar; Chihab, Younes; Mousaid, Nouredine; Oujaoura, Mustapha

    2015-09-01

    The Tifinagh alphabet-IRCAM is the official alphabet of the Amazigh language widely used in North Africa [1]. It includes thirty-one basic letter and two letters each composed of a base letter followed by the sign of labialization. Normalized only in 2003 (Unicode) [2], ICRAM-Tifinagh is a young character repertoire. Which needs more work on all levels. In this context we propose a data set for handwritten Tifinagh characters composed of 1376 image; 43 Image For Each character. The dataset can be used to train a Tifinagh character recognition system, or to extract the meaning characteristics of each character.

  13. Online Farsi Character Recognition Using Structural Features

    Directory of Open Access Journals (Sweden)

    Vahid Ghods

    2012-04-01

    Full Text Available In this paper, grouping and recognition of online Farsi discrete characters are presented according to their structural features. The letters are divided into 9 groups based on the form and structure of their main bodies. After feature extraction, grouping is performed using a decision tree. Final recognition of letters is carried out in each group by delayed strokes. The proposed method is a rapid method in character recognition because time-consuming methods have not been used. Our proposed method was tested on TMU-OFS dataset, and a recognition rate of 94% and 92% was achieved for character grouping and recognition, respectively. The mean processing time for recognizing a letter was 3ms.

  14. Chinese character recognition :history ,status and prospects

    Institute of Scientific and Technical Information of China (English)

    DAI Ruwei; LIU Chenglin; XIAO Baihua

    2007-01-01

    Chinese character recognition (CCR) is an important branch of pattern recognition.It was considered as an extremely difficult problem due to the very large number of categories,complicated structures,similarity between characters,and the variability of fonts or writing styles.Because of its unique technical challenges and great social needs,the last four decades witnessed the intensive research in this field and a rapid increase of successful applications.However,higher recognition performance is continuously needed to improve the existing applications and to exploit new applications.This paper first provides an overview of Chinese character recognition and the properties of Chinese characters.Some important methods and successful results in the history of Chinese character recognition are then summarized.As for classification methods,this article pays special attention to the syntactic-semantic approach for online Chinese character recognition,as well as the metasynthesis approach for discipline crossing.Finally,the remaining problems and the possible solutions are discussed.

  15. Proficient Character Recognition from Images

    National Research Council Canada - National Science Library

    Poornima T M; M Amanullah

    2016-01-01

    .... Two key components of most systems are (i) text detection from images and (ii) text recognition, and many methods have been introduced to design better feature representations and models for both...

  16. Recognition of Telugu characters using neural networks.

    Science.gov (United States)

    Sukhaswami, M B; Seetharamulu, P; Pujari, A K

    1995-09-01

    The aim of the present work is to recognize printed and handwritten Telugu characters using artificial neural networks (ANNs). Earlier work on recognition of Telugu characters has been done using conventional pattern recognition techniques. We make an initial attempt here of using neural networks for recognition with the aim of improving upon earlier methods which do not perform effectively in the presence of noise and distortion in the characters. The Hopfield model of neural network working as an associative memory is chosen for recognition purposes initially. Due to limitation in the capacity of the Hopfield neural network, we propose a new scheme named here as the Multiple Neural Network Associative Memory (MNNAM). The limitation in storage capacity has been overcome by combining multiple neural networks which work in parallel. It is also demonstrated that the Hopfield network is suitable for recognizing noisy printed characters as well as handwritten characters written by different "hands" in a variety of styles. Detailed experiments have been carried out using several learning strategies and results are reported. It is shown here that satisfactory recognition is possible using the proposed strategy. A detailed preprocessing scheme of the Telugu characters from digitized documents is also described.

  17. CHARACTER DETECTION AND RECOGNITION SYSTEM OF BEER BOTTLES

    Institute of Scientific and Technical Information of China (English)

    Shen Bangxing; Wu Wenjun; Zhang Yepeng; Shen Gang; Yang Liangen

    2005-01-01

    An optical imaging system and a configuration characteristic algorithm are presented to reduce the difficulties in extracting intact characters image with weak contrast, in recognizing characters on fast moving beer bottles. The system consists of a hardware subsystem, including a rotating device, CCD, 16 mm focus lens, a frame grabber card, a penetrating lighting and a computer, and a software subsystem. The software subsystem performs pretreatment, character segmentation and character recognition. In the pretreatment, the original image is filtered with preset threshold to remove isolated spots. Then the horizontal projection and the vertical projection are used respectively to retrieve the character segmentation. Subsequently, the configuration characteristic algorithm is applied to recognize the characters. The experimental results demonstrate that this system can recognize the characters on beer bottles accurately and effectively; the algorithm is proven fast, stable and robust, making it suitable in the industrial environment.

  18. Recognition of isolated handprinted characters

    DEFF Research Database (Denmark)

    Martins, Bo

    1996-01-01

    Handprinted characters are of unequal complexity and a common description of all alphabet symbols seems therefore unobtainable. However, letters which confuse human beings and man-made OCR systems usually have approximately the same appearance and may therefore be modeled jointly. We part the set...... is usually too large but can be reduced automatically by the use of a predictive code length or predictive error criterion...

  19. Postprocessing for character recognition using pattern features and linguistic information

    Science.gov (United States)

    Yoshikawa, Takatoshi; Okamoto, Masayosi; Horii, Hiroshi

    1993-04-01

    We propose a new method of post-processing for character recognition using pattern features and linguistic information. This method corrects errors in the recognition of handwritten Japanese sentences containing Kanji characters. This post-process method is characterized by having two types of character recognition. Improving the accuracy of the character recognition rate of Japanese characters is made difficult by the large number of characters, and the existence of characters with similar patterns. Therefore, it is not practical for a character recognition system to recognize all characters in detail. First, this post-processing method generates a candidate character table by recognizing the simplest features of characters. Then, it selects words corresponding to the character from the candidate character table by referring to a word and grammar dictionary before selecting suitable words. If the correct character is included in the candidate character table, this process can correct an error, however, if the character is not included, it cannot correct an error. Therefore, if this method can presume a character does not exist in a candidate character table by using linguistic information (word and grammar dictionary). It then can verify a presumed character by character recognition using complex features. When this method is applied to an online character recognition system, the accuracy of character recognition improves 93.5% to 94.7%. This proved to be the case when it was used for the editorials of a Japanese newspaper (Asahi Shinbun).

  20. Post processing for offline Chinese handwritten character string recognition

    Science.gov (United States)

    Wang, YanWei; Ding, XiaoQing; Liu, ChangSong

    2012-01-01

    Offline Chinese handwritten character string recognition is one of the most important research fields in pattern recognition. Due to the free writing style, large variability in character shapes and different geometric characteristics, Chinese handwritten character string recognition is a challenging problem to deal with. However, among the current methods over-segmentation and merging method which integrates geometric information, character recognition information and contextual information, shows a promising result. It is found experimentally that a large part of errors are segmentation error and mainly occur around non-Chinese characters. In a Chinese character string, there are not only wide characters namely Chinese characters, but also narrow characters like digits and letters of the alphabet. The segmentation error is mainly caused by uniform geometric model imposed on all segmented candidate characters. To solve this problem, post processing is employed to improve recognition accuracy of narrow characters. On one hand, multi-geometric models are established for wide characters and narrow characters respectively. Under multi-geometric models narrow characters are not prone to be merged. On the other hand, top rank recognition results of candidate paths are integrated to boost final recognition of narrow characters. The post processing method is investigated on two datasets, in total 1405 handwritten address strings. The wide character recognition accuracy has been improved lightly and narrow character recognition accuracy has been increased up by 10.41% and 10.03% respectively. It indicates that the post processing method is effective to improve recognition accuracy of narrow characters.

  1. ON­LINE CHARACTER RECOGNITION ADAPTIVELY CONTROLLED BY HANDWRITING QUALITY

    NARCIS (Netherlands)

    Hamanaka, M.; Yamada, K.

    2004-01-01

    On­line character recognition which can adapt to handwriting quality is proposed. In character recognition, it is difficult to recognize both clearly and roughly written characters accurately. For Japanese characters, the number of strokes is often slightly varied when characters are written roughly

  2. ON­LINE CHARACTER RECOGNITION ADAPTIVELY CONTROLLED BY HANDWRITING QUALITY

    NARCIS (Netherlands)

    Hamanaka, M.; Yamada, K.

    2004-01-01

    On­line character recognition which can adapt to handwriting quality is proposed. In character recognition, it is difficult to recognize both clearly and roughly written characters accurately. For Japanese characters, the number of strokes is often slightly varied when characters are written

  3. ON­LINE CHARACTER RECOGNITION ADAPTIVELY CONTROLLED BY HANDWRITING QUALITY

    NARCIS (Netherlands)

    Hamanaka, M.; Yamada, K.

    2004-01-01

    On­line character recognition which can adapt to handwriting quality is proposed. In character recognition, it is difficult to recognize both clearly and roughly written characters accurately. For Japanese characters, the number of strokes is often slightly varied when characters are written roughly

  4. Printed Arabic Character Recognition Using HMM

    Institute of Scientific and Technical Information of China (English)

    Abbas H.Hassin; Xiang-Long Tang; Jia-Feng Liu; Wei Zhao

    2004-01-01

    The Arabic Language has a very rich vocabulary.More than 200 million people speak this language as their native speaking,and over 1 billion people use it in several religion-related activities.In this paper a new technique is presented for recognizing printed Arabic characters.After a word is segmented,each character/word is entirely transformed into a feature vector.The features of printed Arabic characters include strokes and bays in various directions,endpoints,intersection points,loops,dots and zigzags.The word skeleton is decomposed into a number of links in orthographic order,and then it is transferred into a sequence of symbols using vector quantization.Single hidden Markov model has been used for recognizing the printed Arabic characters.Experimental results show that the high recognition rate depends on the number of states in each sample.

  5. Affine Invariant Character Recognition by Progressive Removing

    Science.gov (United States)

    Iwamura, Masakazu; Horimatsu, Akira; Niwa, Ryo; Kise, Koichi; Uchida, Seiichi; Omachi, Shinichiro

    Recognizing characters in scene images suffering from perspective distortion is a challenge. Although there are some methods to overcome this difficulty, they are time-consuming. In this paper, we propose a set of affine invariant features and a new recognition scheme called “progressive removing” that can help reduce the processing time. Progressive removing gradually removes less feasible categories and skew angles by using multiple classifiers. We observed that progressive removing and the use of the affine invariant features reduced the processing time by about 60% in comparison to a trivial one without decreasing the recognition rate.

  6. Nonlinear filtering for character recognition in low quality document images

    Science.gov (United States)

    Diaz-Escobar, Julia; Kober, Vitaly

    2014-09-01

    Optical character recognition in scanned printed documents is a well-studied task, where the captured conditions like sheet position, illumination, contrast and resolution are controlled. Nowadays, it is more practical to use mobile devices for document capture than a scanner. So as a consequence, the quality of document images is often poor owing to presence of geometric distortions, nonhomogeneous illumination, low resolution, etc. In this work we propose to use multiple adaptive nonlinear composite filters for detection and classification of characters. Computer simulation results obtained with the proposed system are presented and discussed.

  7. Using Character Recognition for Plate Localization

    Directory of Open Access Journals (Sweden)

    Lama Hamandi

    2012-10-01

    Full Text Available In this paper, the “character recognition” approach to recognizing a vehicle license plate is used for localizing Saudi license plates. The proposed algorithm filters out all possible objects from the license plate image and focuses on the resulting objects. The coordinates of the center point of the bounding box for these objects is calculated and then possible alignments between these objects are checked. After finding the aligned objects, the recognition algorithms are applied to differentiate the numbers from the letters in the plate.

  8. Chinese character recognition using simulated phosphene maps.

    Science.gov (United States)

    Zhao, Ying; Lu, Yanyu; Zhou, Chuanqing; Chen, Yao; Ren, Qiushi; Chai, Xinyu

    2011-05-01

    A visual prosthetic device may produce phosphene maps in which individual phosphene characteristics can be altered. This study was an investigation of the ability of normally sighted subjects to recognize Chinese characters (CCs) after altering simulated phosphene maps. Thirty volunteers with normal or corrected visual acuity of 20/20 were recruited. CC recognition accuracy and response time were investigated while one parameter was changed (distortion, pixel dropout percentage, pixel size variability, or pixel gray level) or different combinations of three parameters were used. Five hundred CCs consisting of 1 to 16 strokes were used for the character sets. CC recognition accuracy and response times respectively decreased and increased when distortion, dropout, and pixel size variability increased. Gray levels did not significantly affect the results, except when eight levels were used. To maintain an 80% accuracy rate, there should be a distortion index (k) of no more than 0.2 (irregularity), a pixel dropout of 20%, and a pixel size range of 1 to 16 mm (7-112 min arc). Only a combination of a k=0.1 distortion index, a dropout of 10%, and a pixel size range of 1.33 to 12 mm (9.3-84 min arc) achieved a goal of ≥80% accuracy. Distortion, dropout percentage, and pixel size variability have a significant impact on pixelated CC recognition. Although at present the visual ability of prosthesis users is limited, it should be possible to extend this to CC recognition and reading in the future. The results will help visual prosthesis researchers determine the effects of altering phosphene maps and improve outcomes for patients.

  9. A Review of Research on Devnagari Character Recognition

    CERN Document Server

    Dongre, V J

    2011-01-01

    English Character Recognition (CR) has been extensively studied in the last half century and progressed to a level, sufficient to produce technology driven applications. But same is not the case for Indian languages which are complicated in terms of structure and computations. Rapidly growing computational power may enable the implementation of Indic CR methodologies. Digital document processing is gaining popularity for application to office and library automation, bank and postal services, publishing houses and communication technology. Devnagari being the national language of India, spoken by more than 500 million people, should be given special attention so that document retrieval and analysis of rich ancient and modern Indian literature can be effectively done. This article is intended to serve as a guide and update for the readers, working in the Devnagari Optical Character Recognition (DOCR) area. An overview of DOCR systems is presented and the available DOCR techniques are reviewed. The current statu...

  10. Handwritten Bangla Basic and Compound character recognition using MLP and SVM classifier

    CERN Document Server

    Das, Nibaran; Sarkar, Ram; Basu, Subhadip; Kundu, Mahantapas; Nasipuri, Mita

    2010-01-01

    A novel approach for recognition of handwritten compound Bangla characters, along with the Basic characters of Bangla alphabet, is presented here. Compared to English like Roman script, one of the major stumbling blocks in Optical Character Recognition (OCR) of handwritten Bangla script is the large number of complex shaped character classes of Bangla alphabet. In addition to 50 basic character classes, there are nearly 160 complex shaped compound character classes in Bangla alphabet. Dealing with such a large varieties of handwritten characters with a suitably designed feature set is a challenging problem. Uncertainty and imprecision are inherent in handwritten script. Moreover, such a large varieties of complex shaped characters, some of which have close resemblance, makes the problem of OCR of handwritten Bangla characters more difficult. Considering the complexity of the problem, the present approach makes an attempt to identify compound character classes from most frequently to less frequently occurred o...

  11. Comparative Analysis of PSO and GA in Geom-Statistical Character Features Selection for Online Character Recognition

    Directory of Open Access Journals (Sweden)

    Fenwa O.D

    2015-08-01

    Full Text Available Online handwriting recognition today has special interest due to increased usage of the hand held devices and it has become a difficult problem because of the high variability and ambiguity in the character shapes written by individuals. One major problem encountered by researchers in developing character recognition system is selection of efficient features (optimal features. In this paper, a feature extraction technique for online character recognition system was developed using hybrid of geometrical and statistical (Geom-statistical features. Thus, through the integration of geometrical and statistical features, insights were gained into new character properties, since these types of features were considered to be complementary. Several optimization techniques have been used in literature for feature selection in character recognition such as; Ant Colony Optimization Algorithm (ACO, Genetic Algorithm (GA, Particle Swarm Optimization (PSO and Simulated Annealing but comparative analysis of GA and PSO in online character has not been carried out. In this paper, a comparative analysis of performance was made between the GA and PSO in optimizing the Geom-statistical features in online character recognition using Modified Optical Backpropagation (MOBP as classifier. Simulation of the system was done and carried out on Matlab 7.10a. The results generated show that PSO is a well-accepted optimization algorithm in selection of optimal features as it outperforms the GA in terms of number of features selected, training time and recognition accuracy.

  12. Gesture Recognition Using Character Recognition Techniques on Two-dimensional Eigenspace

    OpenAIRE

    大野, 宏; 山本, 正信; Ohno, Hiroshi; Yamamoto, Masanobu

    1999-01-01

    This paper describes a novel method for gesture recognition using character recognition techniques on two-dimensional eigenspace. An image-based approach can capture human body poses in 3D motion from multiple image sequences. The sequence of poses can be reduced into a trajectory on the two-dimensional eigenspace with preserving the main features in gesture, so that the gesture recognition equals the character recognition. Experiments for the gesture recognition using some character recognit...

  13. A comparison study between MLP and convolutional neural network models for character recognition

    Science.gov (United States)

    Ben Driss, S.; Soua, M.; Kachouri, R.; Akil, M.

    2017-05-01

    Optical Character Recognition (OCR) systems have been designed to operate on text contained in scanned documents and images. They include text detection and character recognition in which characters are described then classified. In the classification step, characters are identified according to their features or template descriptions. Then, a given classifier is employed to identify characters. In this context, we have proposed the unified character descriptor (UCD) to represent characters based on their features. Then, matching was employed to ensure the classification. This recognition scheme performs a good OCR Accuracy on homogeneous scanned documents, however it cannot discriminate characters with high font variation and distortion.3 To improve recognition, classifiers based on neural networks can be used. The multilayer perceptron (MLP) ensures high recognition accuracy when performing a robust training. Moreover, the convolutional neural network (CNN), is gaining nowadays a lot of popularity for its high performance. Furthermore, both CNN and MLP may suffer from the large amount of computation in the training phase. In this paper, we establish a comparison between MLP and CNN. We provide MLP with the UCD descriptor and the appropriate network configuration. For CNN, we employ the convolutional network designed for handwritten and machine-printed character recognition (Lenet-5) and we adapt it to support 62 classes, including both digits and characters. In addition, GPU parallelization is studied to speed up both of MLP and CNN classifiers. Based on our experimentations, we demonstrate that the used real-time CNN is 2x more relevant than MLP when classifying characters.

  14. Simple and efficient method for region of interest value extraction from picture archiving and communication system viewer with optical character recognition software and macro program.

    Science.gov (United States)

    Lee, Young Han; Park, Eun Hae; Suh, Jin-Suck

    2015-01-01

    The objectives are: 1) to introduce a simple and efficient method for extracting region of interest (ROI) values from a Picture Archiving and Communication System (PACS) viewer using optical character recognition (OCR) software and a macro program, and 2) to evaluate the accuracy of this method with a PACS workstation. This module was designed to extract the ROI values on the images of the PACS, and created as a development tool by using open-source OCR software and an open-source macro program. The principal processes are as follows: (1) capture a region of the ROI values as a graphic file for OCR, (2) recognize the text from the captured image by OCR software, (3) perform error-correction, (4) extract the values including area, average, standard deviation, max, and min values from the text, (5) reformat the values into temporary strings with tabs, and (6) paste the temporary strings into the spreadsheet. This principal process was repeated for the number of ROIs. The accuracy of this module was evaluated on 1040 recognitions from 280 randomly selected ROIs of the magnetic resonance images. The input times of ROIs were compared between conventional manual method and this extraction module-assisted input method. The module for extracting ROI values operated successfully using the OCR and macro programs. The values of the area, average, standard deviation, maximum, and minimum could be recognized and error-corrected with AutoHotkey-coded module. The average input times using the conventional method and the proposed module-assisted method were 34.97 seconds and 7.87 seconds, respectively. A simple and efficient method for ROI value extraction was developed with open-source OCR and a macro program. Accurate inputs of various numbers from ROIs can be extracted with this module. The proposed module could be applied to the next generation of PACS or existing PACS that have not yet been upgraded. Copyright © 2015 AUR. Published by Elsevier Inc. All rights reserved.

  15. A novel approach for handwritten Devnagari character recognition

    CERN Document Server

    Arora, Sandhya; Bhattacharjee, Debotosh; Nasipuri, Mita

    2010-01-01

    In this paper a method for recognition of handwritten devanagari characters is described. Here, feature vector is constituted by accumulated directional gradient changes in different segments, number of intersections points for the character, type of spine present and type of shirorekha present in the character. One Multi-layer Perceptron with conjugate-gradient training is used to classify these feature vectors. This method is applied to a database with 1000 sample characters and the recognition rate obtained is 88.12%

  16. Handwritten Character Recognition of South Indian Scripts: A Review

    CERN Document Server

    Jomy, John; Kannan, Balakrishnan

    2011-01-01

    Handwritten character recognition is always a frontier area of research in the field of pattern recognition and image processing and there is a large demand for OCR on hand written documents. Even though, sufficient studies have performed in foreign scripts like Chinese, Japanese and Arabic characters, only a very few work can be traced for handwritten character recognition of Indian scripts especially for the South Indian scripts. This paper provides an overview of offline handwritten character recognition in South Indian Scripts, namely Malayalam, Tamil, Kannada and Telungu.

  17. 29 CFR 780.706 - Recognition of character of establishment.

    Science.gov (United States)

    2010-07-01

    ... 29 Labor 3 2010-07-01 2010-07-01 false Recognition of character of establishment. 780.706 Section... Under Section 13(b)(14) Establishment Commonly Recognized As A Country Elevator § 780.706 Recognition of character of establishment. A further requirement for exemption is that the establishment must be “commonly...

  18. Remarks on different reviews of Chinese character recognition

    Institute of Scientific and Technical Information of China (English)

    TANG Yuanyan

    2007-01-01

    This paper gives an introduction and remarks on two review papers for Chinese character recognition.One review is made by Chinese authors,another is from American scientists.They investigate Chinese character from different language environments;they do the research from different points of view.Thus,a more comprehensive view on Chinese character recognition,which is an important branch of pattern recognition,can be provided to the readers.Meantime,one article pays attention to online process,and other paper deals with offiine recognition,which complement each other.

  19. Online Handwritten Character Recognition of Devanagari and Telugu Characters using Support Vector Machines

    OpenAIRE

    Swethalakshmi, H.; Jayaraman, Anitha; Chakravarthy, V. Srinivasa; Sekhar, C. Chandra

    2006-01-01

    http://www.suvisoft.com; A system for recognition of online handwritten characters has been presented for Indian writing systems. A handwritten character is represented as a sequence of strokes whose features are extracted and classied. Support vector machines have been used for constructing the stroke recognition engine. The results have been presented after testing the system on Devanagari and Telugu scripts.

  20. Features fusion based approach for handwritten Gujarati character recognition

    Directory of Open Access Journals (Sweden)

    Ankit Sharma

    2017-02-01

    Full Text Available Handwritten character recognition is a challenging area of research. Lots of research activities in the area of character recognition are already done for Indian languages such as Hindi, Bangla, Kannada, Tamil and Telugu. Literature review on handwritten character recognition indicates that in comparison with other Indian scripts research activities on Gujarati handwritten character recognition are very less.  This paper aims to bring Gujarati character recognition in attention. Recognition of isolated Gujarati handwritten characters is proposed using three different kinds of features and their fusion. Chain code based, zone based and projection profiles based features are utilized as individual features. One of the significant contribution of proposed work is towards the generation of large and representative dataset of 88,000 handwritten Gujarati characters. Experiments are carried out on this developed dataset. Artificial Neural Network (ANN, Support Vector Machine (SVM and Naive Bayes (NB classifier based methods are implemented for handwritten Gujarati character recognition. Experimental results show substantial enhancement over state-of-the-art and authenticate our proposals.

  1. Character recognition using a neural network model with fuzzy representation

    Science.gov (United States)

    Tavakoli, Nassrin; Seniw, David

    1992-01-01

    The degree to which digital images are recognized correctly by computerized algorithms is highly dependent upon the representation and the classification processes. Fuzzy techniques play an important role in both processes. In this paper, the role of fuzzy representation and classification on the recognition of digital characters is investigated. An experimental Neural Network model with application to character recognition was developed. Through a set of experiments, the effect of fuzzy representation on the recognition accuracy of this model is presented.

  2. Handwritten Farsi Character Recognition using Artificial Neural Network

    CERN Document Server

    Ahangar, Reza Gharoie

    2009-01-01

    Neural Networks are being used for character recognition from last many years but most of the work was confined to English character recognition. Till date, a very little work has been reported for Handwritten Farsi Character recognition. In this paper, we have made an attempt to recognize handwritten Farsi characters by using a multilayer perceptron with one hidden layer. The error backpropagation algorithm has been used to train the MLP network. In addition, an analysis has been carried out to determine the number of hidden nodes to achieve high performance of backpropagation network in the recognition of handwritten Farsi characters. The system has been trained using several different forms of handwriting provided by both male and female participants of different age groups. Finally, this rigorous training results an automatic HCR system using MLP network. In this work, the experiments were carried out on two hundred fifty samples of five writers. The results showed that the MLP networks trained by the err...

  3. Character-based Recognition of Simple Word Gesture

    Directory of Open Access Journals (Sweden)

    Paulus Insap Santosa

    2013-11-01

    Full Text Available People with normal senses use spoken language to communicate with others. This method cannot be used by those with hearing and speech impaired. These two groups of people will have difficulty when they try to communicate to each other using their own language. Sign language is not easy to learn, as there are various sign languages, and not many tutors are available. This research focused on a simple word recognition gesture based on characters that form a word to be recognized. The method used for character recognition was the nearest neighbour method. This method identified different fingers using the different markers attached to each finger. Testing a simple word gesture recognition is done by providing a series of characters that make up the intended simple word. The accuracy of a simple word gesture recognition depended upon the accuracy of recognition of each character.

  4. Recognition of handprinted characters for automated cartography A progress report

    Science.gov (United States)

    Lybanon, M.; Brown, R. M.; Gronmeyer, L. K.

    1980-01-01

    A research program for developing handwritten character recognition techniques is reported. The generation of cartographic/hydrographic manuscripts is overviewed. The performance of hardware/software systems is discussed, along with future research problem areas and planned approaches.

  5. Building Hierarchical Representations for Oracle Character and Sketch Recognition.

    Science.gov (United States)

    Jun Guo; Changhu Wang; Roman-Rangel, Edgar; Hongyang Chao; Yong Rui

    2016-01-01

    In this paper, we study oracle character recognition and general sketch recognition. First, a data set of oracle characters, which are the oldest hieroglyphs in China yet remain a part of modern Chinese characters, is collected for analysis. Second, typical visual representations in shape- and sketch-related works are evaluated. We analyze the problems suffered when addressing these representations and determine several representation design criteria. Based on the analysis, we propose a novel hierarchical representation that combines a Gabor-related low-level representation and a sparse-encoder-related mid-level representation. Extensive experiments show the effectiveness of the proposed representation in both oracle character recognition and general sketch recognition. The proposed representation is also complementary to convolutional neural network (CNN)-based models. We introduce a solution to combine the proposed representation with CNN-based models, and achieve better performances over both approaches. This solution has beaten humans at recognizing general sketches.

  6. Machine Recognition of Hand Written Characters using Neural Networks

    CERN Document Server

    Perwej, Yusuf; 10.5120/1819-2380

    2012-01-01

    Even today in Twenty First Century Handwritten communication has its own stand and most of the times, in daily life it is globally using as means of communication and recording the information like to be shared with others. Challenges in handwritten characters recognition wholly lie in the variation and distortion of handwritten characters, since different people may use different style of handwriting, and direction to draw the same shape of the characters of their known script. This paper demonstrates the nature of handwritten characters, conversion of handwritten data into electronic data, and the neural network approach to make machine capable of recognizing hand written characters.

  7. A feature extraction technique based on character geometry for character recognition

    CERN Document Server

    Gaurav, Dinesh Dileep

    2012-01-01

    This paper describes a geometry based technique for feature extraction applicable to segmentation-based word recognition systems. The proposed system extracts the geometric features of the character contour. This features are based on the basic line types that forms the character skeleton. The system gives a feature vector as its output. The feature vectors so generated from a training set, were then used to train a pattern recognition engine based on Neural Networks so that the system can be benchmarked.

  8. Spectral Analysis of Projection Histogram for Enhancing Close matching character Recognition in Malayalam

    CERN Document Server

    Divakaran, Sajilal

    2012-01-01

    The success rates of Optical Character Recognition (OCR) systems for printed Malayalam documents is quite impressive with the state of the art accuracy levels in the range of 85-95% for various. However for real applications, further enhancement of this accuracy levels are required. One of the bottle necks in further enhancement of the accuracy is identified as close-matching characters. In this paper, we delineate the close matching characters in Malayalam and report the development of a specialised classifier for these close-matching characters. The output of a state of the art of OCR is taken and characters falling into the close-matching character set is further fed into this specialised classifier for enhancing the accuracy. The classifier is based on support vector machine algorithm and uses feature vectors derived out of spectral coefficients of projection histogram signals of close-matching characters.

  9. Sunspot drawings handwritten character recognition method based on deep learning

    Science.gov (United States)

    Zheng, Sheng; Zeng, Xiangyun; Lin, Ganghua; Zhao, Cui; Feng, Yongli; Tao, Jinping; Zhu, Daoyuan; Xiong, Li

    2016-05-01

    High accuracy scanned sunspot drawings handwritten characters recognition is an issue of critical importance to analyze sunspots movement and store them in the database. This paper presents a robust deep learning method for scanned sunspot drawings handwritten characters recognition. The convolution neural network (CNN) is one algorithm of deep learning which is truly successful in training of multi-layer network structure. CNN is used to train recognition model of handwritten character images which are extracted from the original sunspot drawings. We demonstrate the advantages of the proposed method on sunspot drawings provided by Chinese Academy Yunnan Observatory and obtain the daily full-disc sunspot numbers and sunspot areas from the sunspot drawings. The experimental results show that the proposed method achieves a high recognition accurate rate.

  10. Handwriting Moroccan regions recognition using Tifinagh character.

    Science.gov (United States)

    El Kessab, B; Daoui, C; Bouikhalene, B; Salouan, R

    2015-09-01

    The territorial organization of Morocco during administratives division of 2009 is based on 16 regions. In this work we will create a system of recognition of handwritten words (names of regions) using the Amazigh language is an official language by the Moroccan Royal Institute of Amazigh Culture (IRCAM) (2003a) [1] such as this language is slightly treated by researchers in pattern recognition field that is why we decided to study this language (El Kessab et al., 2013 [3]; El Kessab et al., 2014 [4]) that knowing the state make a decision to computerize the various public sectors by this language. In this context we propose a data set for handwritten Tifinagh regions composed of 1600 image (100 Image for each region). The dataset can be used in one hand to test the efficiency of the Tifinagh region recognition system in extraction of characteristics significatives and the correct identification of each region in classification phase in the other hand.

  11. Handwriting Moroccan regions recognition using Tifinagh character

    Directory of Open Access Journals (Sweden)

    B. El Kessab

    2015-09-01

    In this context we propose a data set for handwritten Tifinagh regions composed of 1600 image (100 Image for each region. The dataset can be used in one hand to test the efficiency of the Tifinagh region recognition system in extraction of characteristics significatives and the correct identification of each region in classification phase in the other hand.

  12. Handwritten Javanese Character Recognition Using Several Artificial Neural Network Methods

    Directory of Open Access Journals (Sweden)

    Gregorius Satia Budhi

    2015-07-01

    Full Text Available Javanese characters are traditional characters that are used to write the Javanese language. The Javanese language is a language used by many people on the island of Java, Indonesia. The use of Javanese characters is diminishing more and more because of the difficulty of studying the Javanese characters themselves. The Javanese character set consists of basic characters, numbers, complementary characters, and so on. In this research we have developed a system to recognize Javanese characters. Input for the system is a digital image containing several handwritten Javanese characters. Preprocessing and segmentation are performed on the input image to get each character. For each character, feature extraction is done using the ICZ-ZCZ method. The output from feature extraction will become input for an artificial neural network. We used several artificial neural networks, namely a bidirectional associative memory network, a counterpropagation network, an evolutionary network, a backpropagation network, and a backpropagation network combined with chi2. From the experimental results it can be seen that the combination of chi2 and backpropagation achieved better recognition accuracy than the other methods.

  13. Farsi License Plate Detection and Recognition Based on Characters Features

    Directory of Open Access Journals (Sweden)

    Sedigheh Ghofrani

    2011-06-01

    Full Text Available In this paper a license plate detection and recognition system for Iranian private cars is implemented. The proposed license plate localization algorithm is based on region elements analysis which works properly independent of distance (how far a vehicle is, rotation (angle between camera and vehicle, and contrast (being dirty, reflected, or deformed. In addition, more than one car may exist in the image. The proposed method extracts edges and then determines the candidate regions by applying window movement. The region elements analysis includes binarization, character analysis, character continuity analysis and character parallelism analysis. After detecting license plates, we estimate the rotation angle and try to compensate it. In order to identify a detected plate, every character should be recognized. For this purpose, we present 25 features and use them as the input to an artificial neural network classifier. The experimental results show that our proposed method achieves appropriate performance for both detection and recognition of the Iranian license plates.

  14. Combining Multiple Feature Extraction Techniques for Handwritten Devnagari Character Recognition

    CERN Document Server

    Arora, Sandhya; Nasipuri, Mita; Basu, Dipak Kumar; Kundu, Mahantapas

    2010-01-01

    In this paper we present an OCR for Handwritten Devnagari Characters. Basic symbols are recognized by neural classifier. We have used four feature extraction techniques namely, intersection, shadow feature, chain code histogram and straight line fitting features. Shadow features are computed globally for character image while intersection features, chain code histogram features and line fitting features are computed by dividing the character image into different segments. Weighted majority voting technique is used for combining the classification decision obtained from four Multi Layer Perceptron(MLP) based classifier. On experimentation with a dataset of 4900 samples the overall recognition rate observed is 92.80% as we considered top five choices results. This method is compared with other recent methods for Handwritten Devnagari Character Recognition and it has been observed that this approach has better success rate than other methods.

  15. Multifont Arabic Characters Recognition Using HoughTransform and HMM/ANN Classification

    OpenAIRE

    Nadia Ben Amor; Najoua Essoukri Ben Amara

    2006-01-01

    Optical Characters Recognition (OCR) has been an active subject of research since the early days of computers. Despite the age of the subject, it remains one of the most challenging and exciting areas of research in computer science. In recent years it has grown into a mature discipline, producing a huge body of work. Arabic character recognition has been one of the last major languages to receive attention. This is due, in part, to the cursive nature of the task since even printed Arabic cha...

  16. Numeric character recognition method based on fractal dimension

    Science.gov (United States)

    He, Tao; Xie, Yulang; Chen, Jiuyin; Cheng, Longfei; Yuan, Ye

    2013-10-01

    An image processing method based on fractal dimension is proposed in this paper. This method uses fractal dimension to process the character images firstly, and rises the analysis of each grid to the analysis of interrelation between the grids to eliminate interference. Box-counting method is commonly used for calculating fractal dimension of fractal, which uses small box whose side length is r ,that is the topological dimension of the box is d, to cover up the image. Because there are various levels of cavities and cracks, some small boxes are empty and some small boxes cover a part of fractal image which is called non-empty box (here refers to the average gray of the part that contained in the small box is larger than a certain threshold). We note down the number of non-empty boxes, analyze and calculate them. The method is used to image process the polluted characters, which can remove ink and scratches around the contour of the characters and remain basic contour, then the characters can be recognized by using template matching. In computer simulation experiment for polluted character recognition, this method can recognize the polluted characters quickly, which improve the accuracy of the recognition of the polluted characters.

  17. Multifont Arabic Characters Recognition Using HoughTransform and HMM/ANN Classification

    Directory of Open Access Journals (Sweden)

    Nadia Ben Amor

    2006-05-01

    Full Text Available Optical Characters Recognition (OCR has been an active subject of research since the early days of computers. Despite the age of the subject, it remains one of the most challenging and exciting areas of research in computer science. In recent years it has grown into a mature discipline, producing a huge body of work. Arabic character recognition has been one of the last major languages to receive attention. This is due, in part, to the cursive nature of the task since even printed Arabic characters are in cursive form. This paper describes the performance of combining Hough transform and Hidden Markov Models in a multifont Arabic OCR system. Experimental tests have been carried out on a set of 85.000 samples of characters corresponding to 5 different fonts from the most commonly used in Arabic writing. Some promising experimental results are reported.

  18. MODIFIED VIEW BASED APPROACHES FOR HANDWRITTEN TAMIL CHARACTER RECOGNITION

    Directory of Open Access Journals (Sweden)

    S. Sobhana Mari

    2015-08-01

    Full Text Available Finding simple and efficient features for offline hand written character recognition is still an active area of research. In this work, we propose modified view based feature extraction approaches for the recognition of handwritten Tamil characters. In the first approach, the five views of a normalized and binarized character image viz, top, bottom, left, right and front are extracted. Each view is then divided into 16 equal zones and the total numbers of background pixel in each zone are counted. The 80 values so obtained form a feature vector. In the second approach, the normalized and binaraized character images are divided into 16 equal zones. Five views are extracted from each zone and the total number of background pixel in each view is counted, resulting in 80 feature values. Further the above two approaches are modified by employing thinned images instead of the whole image. The extracted features are classified using SVM, MLP and ELM classifier. The discriminative powers of the proposed approaches are compared with that of four popular feature extraction approaches in character recognition. The feature extraction time and classification performances are also compared. The proposed modified approaches results in high classification performance (95.26% with comparatively less feature extraction time.

  19. RECOGNITION METHOD FOR CURSIVE JAPANESE WORD WRITTEN IN LATIN CHARACTERS

    NARCIS (Netherlands)

    Maruyama, K.; Nakano, Y.

    2004-01-01

    This paper proposes a recognition method for cursive Japanese words written in Latin characters. The method integrates multiple classifiers using duplicated can­ didates in multiple classifiers and orders of classifiers to improve the word recog­ nition rate combining their results. In experiments u

  20. Recognition of handwritten characters using local gradient feature descriptors

    NARCIS (Netherlands)

    Surinta, Olarik; Karaaba, Mahir F.; Schomaker, Lambert R.B.; Wiering, Marco A.

    2015-01-01

    Abstract In this paper we propose to use local gradient feature descriptors, namely the scale invariant feature transform keypoint descriptor and the histogram of oriented gradients, for handwritten character recognition. The local gradient feature descriptors are used to extract feature vectors fro

  1. ADAPTIVE CONTEXT PROCESSING IN ON-LINE HANDWRITTEN CHARACTER RECOGNITION

    NARCIS (Netherlands)

    Iwayama, N.; Ishigaki, K.

    2004-01-01

    We propose a new approach to context processing in on-line handwritten character recognition (OLCR). Based on the observation that writers often repeat the strings that they input, we take the approach of adaptive context processing. (ACP). In ACP, the strings input by a writer are automatically

  2. Morphological Awareness Uniquely Predicts Young Children's Chinese Character Recognition.

    Science.gov (United States)

    McBride-Chang, Catherine; Shu, Hua; Zhou, Aibao; Wat, Chun Pong; Wagner, Richard K.

    2003-01-01

    Two unique measures of morphological awareness were orally administered to kindergarten and 2nd-grade Hong Kong Chinese children. Both tasks of morphological awareness predicted unique variance in Chinese character recognition in these children, after controlling for age, phonological awareness, speeded naming, speed of processing, and vocabulary.…

  3. Differential Effects of Phonological Priming on Chinese Character Recognition.

    Science.gov (United States)

    Weekes, B. S.; Chen, M. J.; Lin, Y-B.

    1998-01-01

    Finds phonological priming effects on compound targets (characters containing separate radical components); no evidence of phonological priming on integrated targets (those not containing separate radicals); semantic priming effects on both compound and integrated target recognition, suggesting that phonological and semantic activation are…

  4. Recognition of Characters by Adaptive Combination of Classifiers

    Institute of Scientific and Technical Information of China (English)

    WANG Fei; LI Zai-ming

    2004-01-01

    In this paper, the visual feature space based on the long Horizontals, the long Verticals,and the radicals are given. An adaptive combination of classifiers, whose coefficients vary with the input pattern, is also proposed. Experiments show that the approach is promising for character recognition in video sequences.

  5. RECOGNITION METHOD FOR CURSIVE JAPANESE WORD WRITTEN IN LATIN CHARACTERS

    NARCIS (Netherlands)

    Maruyama, K.; Nakano, Y.

    2004-01-01

    This paper proposes a recognition method for cursive Japanese words written in Latin characters. The method integrates multiple classifiers using duplicated can­ didates in multiple classifiers and orders of classifiers to improve the word recog­ nition rate combining their results. In experiments u

  6. Development of Comprehensive Devnagari Numeral and Character Database for Offline Handwritten Character Recognition

    Directory of Open Access Journals (Sweden)

    Vikas J. Dongre

    2012-01-01

    Full Text Available In handwritten character recognition, benchmark database plays an important role in evaluating the performance of various algorithms and the results obtained by various researchers. In Devnagari script, there is lack of such official benchmark. This paper focuses on the generation of offline benchmark database for Devnagari handwritten numerals and characters. The present work generated 5137 and 20305 isolated samples for numeral and character database, respectively, from 750 writers of all ages, sex, education, and profession. The offline sample images are stored in TIFF image format as it occupies less memory. Also, the data is presented in binary level so that memory requirement is further reduced. It will facilitate research on handwriting recognition of Devnagari script through free access to the researchers.

  7. Lexicon Reduction for Urdu/Arabic Script Based Character Recognition: A Multilingual OCR

    Directory of Open Access Journals (Sweden)

    Saeeda Naz

    2016-04-01

    Full Text Available Arabic script character recognition is challenging task due to complexity of the script and huge number of ligatures. We present a method for the development of multilingual Arabic script OCR (Optical Character Recognition and lexicon reduction for Arabic Script and its derivative languages. The objective of the proposed method is to overcome the large dataset Urdu and similar scripts by using GCT (Ghost Character Theory concept. Arabic and its sibling script languages share the similar character dataset i.e. the character set are difference in diacritic and writing styles like Naskh or Nasta?liq. Based on the proposed method, the lexicon for Arabic and Arabic script based languages can be minimized approximately up to 20 times. The proposed multilingual Arabic script OCR approach have been evaluated for online Arabic and its derivative language like Urdu using BPNN. The result showed that proposed method helps to not only the reduction of lexicon but also helps to develop the Multilanguage character recognition system for Arabic Script.

  8. Character recognition of Japanese newspaper headlines with graphical designs

    Science.gov (United States)

    Sawaki, Minako; Hagita, Norihiro

    1996-03-01

    Graphical designs are often used in Japanese newspaper headlines to indicate hot articles. However, conventional OCR software seldom recognizes characters in such headlines because of the difficulty of removing the designs. This paper proposes a method that recognizes these characters without needing removal of the graphical designs. First, the number of text-line regions and the averaged character heights are roughly extracted from the local distribution of the black and white runs observed in a rectangular window while the window is shifted pixel- by-pixel along the direction of the text-line. Next, normalized text-line regions are yielded by normalizing their heights to the height of binary reference patterns in a dictionary. Next, displacement matching is applied to the normalized text-line region for character recognition. A square window at each position is matched against binary reference patterns while being shifted pixel-by-pixel along the direction of the text-line. The complementary similarity measure, which is robust against graphical designs, is used as a discriminant function. When the maximum similarity value at each position exceeds the threshold, which is automatically determined from the degree of degradation in the square window, the character category of this similarity value is specified as a recognized category. Experimental results for fifty Japanese newspaper headlines show that the method achieves recognition rates of over 90%, much higher than a conventional method (17%).

  9. Tifinagh Character Recognition Using Geodesic Distances, Decision Trees & Neural Networks

    Directory of Open Access Journals (Sweden)

    O.BENCHAREF

    2011-09-01

    Full Text Available The recognition of Tifinagh characters cannot be perfectly carried out using the conventional methods which are based on the invariance, this is due to the similarity that exists between some characters which differ from each other only by size or rotation, hence the need to come up with new methods to remedy this shortage. In this paper we propose a direct method based on the calculation of what is called Geodesic Descriptors which have shown significant reliability vis-à-vis the change of scale, noise presence and geometric distortions. For classification, we have opted for a method based on the hybridization of decision trees and neural networks.

  10. On the Performance Improvement of Devanagari Handwritten Character Recognition

    Directory of Open Access Journals (Sweden)

    Pratibha Singh

    2015-01-01

    Full Text Available The paper is about the application of mini minibatch stochastic gradient descent (SGD based learning applied to Multilayer Perceptron in the domain of isolated Devanagari handwritten character/numeral recognition. This technique reduces the variance in the estimate of the gradient and often makes better use of the hierarchical memory organization in modern computers. L2-weight decay is added on minibatch SGD to avoid overfitting. The experiments are conducted firstly on the direct pixel intensity values as features. After that, the experiments are performed on the proposed flexible zone based gradient feature extraction algorithm. The results are promising on most of the standard dataset of Devanagari characters/numerals.

  11. Recognition-based online Kurdish character recognition using hidden Markov model and harmony search

    Directory of Open Access Journals (Sweden)

    Rina D. Zarro

    2017-04-01

    Full Text Available In this paper a hidden Markov model and harmony search algorithms are combined for writer independent online Kurdish character recognition. The Markov model is integrated as an intermediate group classifier instead of a main character classifier/recognizer as in most of previous works. Markov model is used to classify each group of characters, according to their forms, into smaller sub groups based on common directional feature vector. This process reduced the processing time taken by the later recognition stage. The small number of candidate characters are then processed by harmony search recognizer. The harmony search recognizer uses a dominant and common movement pattern as a fitness function. The objective function is used to minimize the matching score according to the fitness function criteria and according to the least score for each segmented group of characters. Then, the system displays the generated word which has the lowest score from the generated character combinations. The system was tested on a dataset of 4500 words structured with 21,234 characters in different positions or forms (isolated, start, middle and end. The system scored 93.52% successful recognition rate with an average of 500 ms. The system showed a high improvement in recognition rate when compared to similar systems that use HMM as its main recognizer.

  12. Improved Approach Based on SVM for License Plate Character Recognition

    Institute of Scientific and Technical Information of China (English)

    WANG Xiao-hua; WANG Xiao-guang

    2005-01-01

    An improved approach based on support vector machine (SVM) called the center distance ratio method is presented for license plate character recognition. First the support vectors are pre-extracted. A minimal set called the margin vector set, which contains all support vectors, is extracted. These margin vectors compose new training data and construct the classifier by using the general SVM optimized. The experimental results show that the improved SVM method does well at correct rate and training speed.

  13. Gaussian process style transfer mapping for historical Chinese character recognition

    Science.gov (United States)

    Feng, Jixiong; Peng, Liangrui; Lebourgeois, Franck

    2015-01-01

    Historical Chinese character recognition is very important to larger scale historical document digitalization, but is a very challenging problem due to lack of labeled training samples. This paper proposes a novel non-linear transfer learning method, namely Gaussian Process Style Transfer Mapping (GP-STM). The GP-STM extends traditional linear Style Transfer Mapping (STM) by using Gaussian process and kernel methods. With GP-STM, existing printed Chinese character samples are used to help the recognition of historical Chinese characters. To demonstrate this framework, we compare feature extraction methods, train a modified quadratic discriminant function (MQDF) classifier on printed Chinese character samples, and implement the GP-STM model on Dunhuang historical documents. Various kernels and parameters are explored, and the impact of the number of training samples is evaluated. Experimental results show that accuracy increases by nearly 15 percentage points (from 42.8% to 57.5%) using GP-STM, with an improvement of more than 8 percentage points (from 49.2% to 57.5%) compared to the STM approach.

  14. Progress in Gujarati Document Processing and Character Recognition

    Science.gov (United States)

    Dholakia, Jignesh; Negi, Atul; Mohan, S. Rama

    Gujarati is an Indic script similar in appearance to other Indo-Aryan scripts. Printed Gujarati script has a rich literary heritage. From an OCR perspective it needs a different treatment due to some of its peculiarities. Research on Gujarati OCR is a recent development as compared to OCR research on many other Indic scripts. Here, in this chapter we present a detailed account of the state of the art of Gujarati document analysis and character recognition. We begin with approaches to zone boundary detection, necessary for the isolation of words and character segmentation and recognition. We show results of various feature extraction techniques such as fringe maps, discrete cosine transform, and wavelets. Zone information and aspect ratios are also used for classification. We present recognition results with two types of classifiers, viz., nearest neighbor classifier and artificial neural networks. Results of experiments wherein various combinations of feature extraction methods with classifiers are also presented. We find that general regression neural network with wavelets feature gives best results with significant time saving in training. Since Indic scripts require syllabic reconstruction from OCR components, a procedure for text generation from the recognized glyph sequences and a method for post-processing is also described.

  15. Automated Degradation Diagnosis in Character Recognition System Subject to Camera Vibration

    Directory of Open Access Journals (Sweden)

    Chunmei Liu

    2014-01-01

    Full Text Available Degradation diagnosis plays an important role for degraded character processing, which can tell the recognition difficulty of a given degraded character. In this paper, we present a framework for automated degraded character recognition system by statistical syntactic approach using 3D primitive symbol, which is integrated by degradation diagnosis to provide accurate and reliable recognition results. Our contribution is to design the framework to build the character recognition submodels corresponding to degradation subject to camera vibration or out of focus. In each character recognition submodel, statistical syntactic approach using 3D primitive symbol is proposed to improve degraded character recognition performance. In the experiments, we show attractive experimental results, highlighting the system efficiency and recognition performance by statistical syntactic approach using 3D primitive symbol on the degraded character dataset.

  16. On-Line Recognition Of Cursive Korean Characters By Descriptions Of Basic Character Patterns And Their Connected Patterns

    Science.gov (United States)

    Lee, Heedong; Nakajima, Masayuki; Agui, Takeshi

    1988-10-01

    The present paper reports an on-line recognition method of cursive Korean characters. In the present method, we treat a Korean character pattern as a finite sequence of basic character patterns. After extracting candidate basic character patterns from an input character pattern, we determine basic character patterns making a Korean character from the candidates by connecting processing. We described basic character patterns and their connected patterns used in the present method according to their features. By extracting and connecting basic character patterns based on the descriptions, we improve description ability of patterns and processing speed. Precise description ability of patterns and extracting candidates can remove unstable writing movements and can separate strokes stably.

  17. Handwritten Javanese Character Recognition Using Several Artificial Neural Network Methods

    OpenAIRE

    Gregorius Satia Budhi; Rudy Adipranata

    2015-01-01

    Javanese characters are traditional characters that are used to write the Javanese language. The Javanese language is a language used by many people on the island of Java, Indonesia. The use of Javanese characters is diminishing more and more because of the difficulty of studying the Javanese characters themselves. The Javanese character set consists of basic characters, numbers, complementary characters, and so on. In this research we have developed a system to recognize Javanese characters....

  18. Online Handwritten Sanskrit Character Recognition Using Support Vector Classification

    Directory of Open Access Journals (Sweden)

    Prof. Sonal P.Patil

    2014-05-01

    Full Text Available Handwritten recognition has been one of the active and challenging research areas in the field of image processing. In this Paper, we are going to analyses feature extraction technique to recognize online handwritten Sanskrit word using preprocessing, segmentation. However, most of the current work in these areas is limited to English and a few oriental languages. The lack of efficient solutions for Indic scripts and languages such as Sanskrit has disadvantaged information extraction from a large body of documents of cultural and historical importance. Here we use Freeman chain code (FCC as the representation technique of an image character. Chain code gives the boundary of a character image in which the codes represents the direction of where is the location of the next pixel. Randomized algorithm is used to generate the FCC. After that, features vector is built. The criterion of features toinput the classification is the chain code that converted to various features. And segmentation is applied to evaluate the possible segmentation zone. Accordingly, several generations are performed to evaluate the individuals with maximum fitness value. Support vector machine (SVM is chosen for the classification step.

  19. Character-level neural network for biomedical named entity recognition.

    Science.gov (United States)

    Gridach, Mourad

    2017-06-01

    Biomedical named entity recognition (BNER), which extracts important named entities such as genes and proteins, is a challenging task in automated systems that mine knowledge in biomedical texts. The previous state-of-the-art systems required large amounts of task-specific knowledge in the form of feature engineering, lexicons and data pre-processing to achieve high performance. In this paper, we introduce a novel neural network architecture that benefits from both word- and character-level representations automatically, by using a combination of bidirectional long short-term memory (LSTM) and conditional random field (CRF) eliminating the need for most feature engineering tasks. We evaluate our system on two datasets: JNLPBA corpus and the BioCreAtIvE II Gene Mention (GM) corpus. We obtained state-of-the-art performance by outperforming the previous systems. To the best of our knowledge, we are the first to investigate the combination of deep neural networks, CRF, word embeddings and character-level representation in recognizing biomedical named entities. Copyright © 2017 Elsevier Inc. All rights reserved.

  20. Optimizing Statistical Character Recognition Using Evolutionary Strategies to Recognize Aircraft Tail Numbers

    Directory of Open Access Journals (Sweden)

    Antonio Berlanga

    2004-07-01

    Full Text Available The design of statistical classification systems for optical character recognition (OCR is a cumbersome task. This paper proposes a method using evolutionary strategies (ES to evolve and upgrade the set of parameters in an OCR system. This OCR is applied to identify the tail number of aircrafts moving on the airport. The proposed approach is discussed and some results are obtained using a benchmark data set. This research demonstrates the successful application of ES to a difficult, noisy, and real-world problem.

  1. A character recognition scheme based on object oriented design for Tibetan buddhist texts

    Directory of Open Access Journals (Sweden)

    Chen-Yuan Liu

    2007-12-01

    Full Text Available The purpose of this study is to develop a plausible method to code and compile Buddhist texts from original Tibetan scripts into Romanized form. Using GUI (Graphical User Interface based on Object Oriented Design, a dictionary of Tibetan characters can be easily made for Buddhist literature researchers. It is hoped that a computer system capable of highly accurate character recognition will be actively used by all scholars engaged in Buddhist literature research. In the present study, an efficient automatic recognition method for Tibetan characters is established. The result of the experiments performed is that the recognition rate achieved is 99.4% for 28,954 characters.

  2. The study on normalization algorithm applied to the character recognition system

    Science.gov (United States)

    Wang, Jingzhong; Xu, Xiaoqing; Hu, Beibei

    2013-03-01

    In this paper, it's research hard on the normalization algorithm of image preprocessing. It proposes that normalize the size of a single character at first, and then thin this character, make an amendment to the framework image at last. Experimental results indicate that this method is validate and lays a solid foundation for consequence processing of the Chinese character recognition.

  3. Wavelet packet based feature extraction and recognition of license plate characters

    Institute of Scientific and Technical Information of China (English)

    HUANG Wei; LU Xiaobo; LING Xiaojing

    2005-01-01

    To study the characteristics of license plate characters recognition, this paper proposes a method for feature extraction of license plate characters based on two-dimensional wavelet packet. We decompose license plate character images with two dimensional-wavelet packet and search for the optimal wavelet packet basis. This paper presents a criterion of searching for the optimal wavelet packet basis, and a practical algorithm. The obtained optimal wavelet packet basis is used as the feature of license plate character, and a BP neural network is used to classify the character.The testing results show that the proposed method achieved higher recognition rate than the traditional methods.

  4. A NOVEL FEATURE SET FOR RECOGNITION OF SIMILAR SHAPED HANDWRITTEN HINDI CHARACTERS USING MACHINE LEARNING

    OpenAIRE

    Sheetal Dabra; Sunil Agrawal; Rama Krishna Challa

    2011-01-01

    The growing need of handwritten Hindi character recognition in Indian offices such as passport, railway etc, has made it a vital area of research. Similar shaped characters are more prone to misclassification. In this paper four Machine Learning (ML) algorithms namely Bayesian Network, Radial Basis Function Network (RBFN), Multilayer Perceptron (MLP), and C4.5 Decision Tree are used for recognition of Similar Shaped Handwritten Hindi Characters (SSHHC) and their performance is ...

  5. A MULTISET APPROACH FOR RECOGNITION OF HANDWRITTEN CHARACTERS USING PUZZLE PIECES

    Directory of Open Access Journals (Sweden)

    Ashlin Deepa R.N

    2012-07-01

    Full Text Available Image pattern matching is one of the most widely used techniques in character recognition. A pattern is the description of an object. Although a large number of papers have been reported on handwritten character recognition, it is still a very challenging problem. Recognition of characters is based on pattern classification. In this paper a hybrid approach is proposed using fuzzy technique and multiset comparison to recognize handwritten characters. Fuzzy technique is used to measure the variations in the features of handwritten numerals to form strings of character. Features are selected from the preprocessed image and the feature is labeled using fuzzy logic. Strings of a character are formed from these labeled primitives. Each string is divided into a multiset of puzzle pieces by repeatedly applying a mask which is comprised of all ones. The string is padded with anchors at the beginning and end. The mask is placed over the string, beginning at a certain character, and reading off all characters corresponding to 1 bit in the mask, thus producing one puzzle piece. To divide a string into multiset of puzzle pieces, the mask is applied at all shifts in the string starting at each character. Thus for each prototype character, we associate a multiset of puzzle pieces, which form the database. The multiset of puzzle pieces of an unknown character is constructed and compared with the same in the database, leading to the identification of the unknown character.

  6. Stroke Detector and Structure Based Models for Character Recognition: A Comparative Study.

    Science.gov (United States)

    Shi, Cun-Zhao; Gao, Song; Liu, Meng-Tao; Qi, Cheng-Zuo; Wang, Chun-Heng; Xiao, Bai-Hua

    2015-12-01

    Characters, which are man-made symbols composed of strokes arranged in a certain structure, could provide semantic information and play an indispensable role in our daily life. In this paper, we try to make use of the intrinsic characteristics of characters and explore the stroke and structure-based methods for character recognition. First, we introduce two existing part-based models to recognize characters by detecting the elastic strokelike parts. In order to utilize strokes of various scales, we propose to learn the discriminative multi-scale stroke detector-based representation (DMSDR) for characters. However, the part-based models and DMSDR need to manually label the parts or key points for training. In order to learn the discriminative stroke detectors automatically, we further propose the discriminative spatiality embedded dictionary learning-based representation (DSEDR) for character recognition. We make a comparative study of the performance of the tree-structured model (TSM), mixtures-of-parts TSM, DMSDR, and DSEDR for character recognition on three challenging scene character recognition (SCR) data sets as well as two handwritten digits recognition data sets. A series of experiments is done on these data sets with various experimental setup. The experimental results demonstrate the suitability of stroke detector-based models for recognizing characters with deformations and distortions, especially in the case of limited training samples.

  7. Limited Top-Down Influence from Recognition to Same-Different Matching of Chinese Characters.

    Science.gov (United States)

    Chang, Jennifer; Zhou, Yifeng; Liu, Zili

    2016-01-01

    We investigated the extent to which recognition of Chinese characters influenced same-different matching performance that did not require recognition. In each experimental trial, two partially occluded characters were shown sequentially, and participants decided whether or not they were the same. The two characters were either both upright or both inverted and mirror-reflected. The participants' Chinese reading fluency spanned the full range, from not knowing any characters to native speakers. The participants who could recognize some characters (defined as readers) were subsequently tested with character recognition in a naming task. Interestingly, although the readers' recognition accuracies well correlated with their years of Chinese language schooling, they were uncorrelated with the matching accuracies in the same-different task with upright characters. The only indication of top-down influence was the readers' higher accuracy in matching upright than inverted and reflected characters. However, the magnitude of this effect was small, to the extent that the average same-different accuracies were comparable for readers and non-readers alike. This small effect was further confirmed with native speakers in China, who should give rise to the largest possible effect. We conclude that top-down influence from character recognition was present but very limited, at least with the task and stimuli used.

  8. A contour distance-based approach for multi-oriented and multi-sized character recognition

    Indian Academy of Sciences (India)

    U Pal; N Tripathy

    2009-10-01

    In this paper, we propose a novel scheme towards the recognition of multi-oriented and multi-sized isolated characters of printed script. For recognition, at first, distances of the outer contour points from the centroid of the individual characters are calculated and these contour distances are then arranged in a particular order to get size and rotation invariant feature. Next, based on the arranged contour distances, the features are derived from different class of characters. Finally, we use these derived features of the characters to statistically compare the features of the input character for recognition. We have tested our scheme on printed Bangla and Devnagari multi-oriented characters and we obtained encouraging results.

  9. Recognition of vertical vowel graphemes of Korean characters based on combination of vowel graphemes

    Institute of Scientific and Technical Information of China (English)

    崔荣一; 洪炳熔

    2002-01-01

    Korean characters consist of 2-dimensional-distributed consonantal and vowel graphemes. The pur-pose of reducing the 2-dimensional characteristics of Korean characters to linear arrangements at early stage ofcharacter recognition is to decrease the complexity of following recognition task. By defining the identificationcodes for the vowel graphemes of Korean characters, the rules for combination of vowel graphemes are estab-lished, and a recognition algorithm based on the rules for combination of vowel graphemes, is therefore proposedfor vertical vowel graphemes. The algorithm has been proved feasilbe through demonstrating simulations.

  10. Parallel optical Walsh expansion in a pattern recognition preprocessor using planar microlens array

    Science.gov (United States)

    Murashige, Kimio; Akiba, Atsushi; Baba, Toshihiko; Iga, Kenichi

    1992-05-01

    A parallel optical processor developed for a pattern recognition system using a planar microlens array and a Walsh orthogonal expansion spatial filter is developed. The parallel optical Walsh expansion of multiple images made by the planar microlens array with good accuracy, which assures 99-percent recognition of simple numeral characters in the system, is demonstrated. A novel selection method of Walsh expansion coefficients is proposed in order to enlarge the tolerance of the recognition rate against the deformation of input patterns.

  11. An approach to offline handwritten Chinese character recognition based on segment evaluation of adaptive duration

    Institute of Scientific and Technical Information of China (English)

    李国宏; 施鹏飞

    2004-01-01

    This paper presents a methodology for off-line handwritten Chinese character recognition based on mergence of consecutive segments of adaptive duration. The handwritten Chinese character string is partitioned into a sequence of consecutive segments, which are combined to implement dissimilarity evaluation within a sliding window whose durations are determined adaptively by the integration of shapes and context of evaluations. The average stroke width is estimated for the handwritten Chinese character string, and a set of candidate character segmentation boundaries is found by using the integration of pixel and stroke features. The final decisions on segmentation and recognition are made under minimal arithmetical mean dissimilarities. Experiments proved that the proposed approach of adaptive duration outperforms the method of fixed duration, and is very effective for the recognition of overlapped, broken, touched, loosely configured Chinese characters.

  12. An approach to offline handwritten Chinese character recognition based on segment evaluation of adaptive duration

    Institute of Scientific and Technical Information of China (English)

    李国宏; 施鹏飞

    2004-01-01

    This paper presents a methodology for off-line handwritten Chinese character recognition based on mergence of consecutive segments of adaptive duration. The handwritten Chinese character string is partitioned into a sequence of consecutive segments,which are combined to implement dissimilarity evaluation within a sliding window whose durations are determined adaptively by the integration of shapes and context of evaluations. The average stroke width is estimated for the handwritten Chinese character string,and a set of candidate character segmentation boundaries is found by using the integration of pixel and stroke features. The final decisions on segmentation and recognition are made under minimal arithmetical mean dissimilarities. Experiments proved that the proposed approach of adaptive duration outperforms the method of fixed duration,and is very effective for the recognition of overlapped,broken,touched,loosely configured Chinese characters.

  13. Multi-level post-processing for Korean character recognition using morphological analysis and linguistic evaluation

    CERN Document Server

    Lee, G; Yoo, J H; Lee, Geunbae; Lee, Jong-Hyeok; Yoo, JinHee

    1996-01-01

    Most of the post-processing methods for character recognition rely on contextual information of character and word-fragment levels. However, due to linguistic characteristics of Korean, such low-level information alone is not sufficient for high-quality character-recognition applications, and we need much higher-level contextual information to improve the recognition results. This paper presents a domain independent post-processing technique that utilizes multi-level morphological, syntactic, and semantic information as well as character-level information. The proposed post-processing system performs three-level processing: candidate character-set selection, candidate eojeol (Korean word) generation through morphological analysis, and final single eojeol-sequence selection by linguistic evaluation. All the required linguistic information and probabilities are automatically acquired from a statistical corpus analysis. Experimental results demonstrate the effectiveness of our method, yielding error correction r...

  14. Feature Dimension Reduction of NaXi Pictographs Characters Recognition based on LDA

    Directory of Open Access Journals (Sweden)

    Hai Guo

    2012-11-01

    Full Text Available As a kind of pictographic character, Naxi pictographs character has received little academic attention. Proposing dimension reduction method of Naxi pictographs characters on the basis of LDA (Linear Discriminant Analysis, this paper thus makes an in-depth study of feature dimension reduction, an important issue in the recognition of Naxi pictographs characters. By constructing a recognition sample library involving four features of grid feature, permeability number feature, moment invariant feature, and directional element feature (DEF, 50% of data are selected from sample library as training set and testing set respectively. Two dimension reduction methods of LDA and FA (Factor Analysis are applied to dimension reduction experiment of features of Naxi pictographs characters. The experiment result proves LDA method to be significantly superior to FA method, as LDA method could still maintain a 99% recognition precision when the dimension is reduced to 10% of the original dimension.

  15. Sequential neural network combination for degraded machine-printed character recognition

    Science.gov (United States)

    Namane, Abderrahmane; Arezki, Madjid; Guessoum, Abderrezak; Soubari, El Houssine; Meyrueis, Patrick P.; Bruynooghe, Michel M.

    2005-01-01

    This paper presents an OCR method that combines Hopfield network with two layer perceptron for degraded printed character recognition. Hopfield network stores 35 prototype characters used as main classes. After the pre-processing, an image of a character is given to Hopfield network which can yield after a fixed iteration number, a pattern that is subsquently fed to MLP for classification. The main idea is to enhance or restore such degraded character images with Hopfield model at different iteration number for recognition accuracy applied to poor quality bank check. We report experimental results for a comparison of three neural architectures: the Hopfield network, the MLP-based classifier and the proposed combined architecture. Classification accuracy for ten digits and twenty five alphabetic characters from a single font is also studied in the presence of additive Gaussian noise. The paper reports 100% recognition rate at different levels of noise. Experimental results show an achievement of 99.35% of recognition rate on poor quality bank check characters, which confirm that the proposed approach can be successfully used for effective degraded printed character recognition.

  16. CHARACTER RECOGNITION BY MATCHING SEQUENCES OF PSEUDO­STROKE POSITIONS AND DIRECTIONS

    NARCIS (Netherlands)

    Xue, H.; Givindaraju, V.

    2004-01-01

    Chain­coded contours are informative in off­line character recognition. As approximations to contours, sequences of pseudo­strokes consisting of both positional and directional information make up feature vectors for character images. In order to carry out fast pattern matching, a scheme of generati

  17. A modular neural network classifier for the recognition of occluded characters in automatic license plate reading

    NARCIS (Netherlands)

    Nijhuis, JAG; Broersma, A; Spaanenburg, L; Ruan, D; Dhondt, P; Kerre, EE

    2002-01-01

    Occlusion is the most common reason for lowered recognition yield in free-flow license-plate reading systems. (Non-)occluded characters can readily be learned in separate neural networks but not together. Even a small proportion of occluded characters in the training set will already significantly r

  18. CHARACTER RECOGNITION BY MATCHING SEQUENCES OF PSEUDO­STROKE POSITIONS AND DIRECTIONS

    NARCIS (Netherlands)

    Xue, H.; Givindaraju, V.

    2004-01-01

    Chain­coded contours are informative in off­line character recognition. As approximations to contours, sequences of pseudo­strokes consisting of both positional and directional information make up feature vectors for character images. In order to carry out fast pattern matching, a scheme of

  19. FEATURE SELECTION USING GENETIC ALGORITHMS FOR HANDWRITTEN CHARACTER RECOGNITION

    NARCIS (Netherlands)

    Kim, G.; Kim, S.

    2004-01-01

    A feature selection method using genetic algorithms which are suitable means for selecting appropriate set of features from ones with huge dimension is proposed. SGA (Simple Genetic Algorithm) and its modified methods are applied to improve the recognition speed as well as the recognition accuracy.

  20. Modality effect in false recognition: evidence from Chinese characters.

    Science.gov (United States)

    Mao, Wei Bin; Yang, Zhi Liang; Wang, Lin Song

    2010-02-01

    Using the Deese/Roediger-McDermott (DRM) false memory method, Smith and Hunt ( 1998 ) first reported the modality effect on false memory and showed that false recall from DRM lists was lower following visual study than following auditory study, which led to numerous studies on the mechanism of modality effect on false memory and provided many competing explanations. In the present experiment, the authors tested the modality effect in false recognition by using a blocked presentation condition and a random presentation condition. The present experiment found a modality effect different from the results of the previous research; namely, false recognition was shown to be greater following visual study than following auditory study, especially in the blocked presentation condition rather than in the random presentation condition. The authors argued that this reversed modality effect may be due to different encoding and processing characteristics between Chinese characters and English words. Compared with English words, visual graphemes of critical lures in Chinese lists are likely to be activated and encoded in participants' minds, thus it is more difficult for participants to discriminate later inner graphemes from those items presented in visual modality. Hence visual presentation could lead to more false recognition than auditory presentation in Chinese lists. The results in the present experiment demonstrated that semantic activation occurring during the encoding and retrieve phases played an important role in modality effect in false recognition, and our findings might be explained by the activation-monitoring account. Utilisant la méthode de fausse mémoire de Deese/Roediger-McDermott (DRM), Smith et Hunt ( 1998 ) ont d'abord rendu compte de l'effet de modalité sur la fausse mémoire et ils ont montré que le faux rappel à partir des listes de DRM était plus faible suivant une étude visuelle plutôt qu'une étude auditive. Ceci a mené à plusieurs

  1. Multi-script handwritten character recognition : Using feature descriptors and machine learning

    NARCIS (Netherlands)

    Surinta, Olarik

    2016-01-01

    Handwritten character recognition plays an important role in transforming raw visual image data obtained from handwritten documents using for example scanners to a format which is understandable by a computer. It is an important application in the field of pattern recognition, machine learning and a

  2. Multi-script handwritten character recognition : Using feature descriptors and machine learning

    NARCIS (Netherlands)

    Surinta, Olarik

    2016-01-01

    Handwritten character recognition plays an important role in transforming raw visual image data obtained from handwritten documents using for example scanners to a format which is understandable by a computer. It is an important application in the field of pattern recognition, machine learning and

  3. A New Linguistic Decoding Method for Online Handwritten Chinese Character Recognition

    Institute of Scientific and Technical Information of China (English)

    徐志明; 王晓龙

    2000-01-01

    This paper presents a new linguistic decoding method for online handwritten Chinese character recognition. The method employs a hybrid language model which combines N-gram and linguistic rules by rule quantification technique.The linguistic decoding algorithm consists of three stages: word lattice construction,the optimal sentence hypothesis search and self-adaptive learning mechanism. The technique has been applied to palmtop computer's online handwritten Chinese character recognition. Samples containing millions of characters were used to test the linguistic decoder. In the open experiment, accuracy rate up to 92% is achieved, and the error rate is reduced by 68%.

  4. ERPs reveal sub-lexical processing in Chinese character recognition.

    Science.gov (United States)

    Wu, Yan; Mo, Deyuan; Tsang, Yiu-Kei; Chen, Hsuan-Chih

    2012-04-18

    The present study used ERPs and a lexical decision task to explore the roles of position-general and position-specific radicals and their relative time courses in processing Chinese characters. Two types of radical frequency were manipulated: the number of characters containing a specific radical irrespective of position (i.e., radical frequency or RF) and the number of characters containing a specific radical at a particular position (i.e., position-specific radical frequency or PRF). The PRF effect was found to be associated with P150, P200, and N400, whereas the RF effect was associated with P200. These results suggest that both position-general and position-specific radicals could influence character processing, but the effect of position-specific radicals appeared earlier and lasted longer than that of position-general radicals. These findings are interpreted in terms of the specific orthographic properties of the sub-lexical components of Chinese characters. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

  5. Study on character recognition of Naxi Dongba hieroglyphs

    Institute of Scientific and Technical Information of China (English)

    WANG; Haiyan; WANG; Hongjun; XU; Xiaoli

    2016-01-01

    Naxi Dongba hieroglyphs of China are the only living hieroglyphs world widely which still in use.There are thousands of manuscripts written in Dongba hieroglyphs scattering in different counties for history reason.For culture protection and inheritance,those manuscripts are in urgent need to be recognized and organized quickly.This paper focuses on the recognition of Naxi Dongba hieroglyphs by using coarse grid method to extract features and using support vector machine to classify.The designed Experiment shows that the method performs better than the commonly used clustering method in recognition accuracy in recognition of Naxi Dongba hieroglyphs.This method also provides some experience for recognition of other hieroglyphs.

  6. Transfer of Perceptual Expertise: The Case of Simplified and Traditional Chinese Character Recognition.

    Science.gov (United States)

    Liu, Tianyin; Chuk, Tin Yim; Yeh, Su-Ling; Hsiao, Janet H

    2016-11-01

    Expertise in Chinese character recognition is marked by reduced holistic processing (HP), which depends mainly on writing rather than reading experience. Here we show that, while simplified and traditional Chinese readers demonstrated a similar level of HP when processing characters shared between the simplified and traditional scripts, simplified Chinese readers were less holistic than traditional Chinese readers in perceiving simplified characters; this effect depended mainly on their writing rather than reading performance. However, the two groups did not differ in HP of traditional characters, regardless of their difference in reading and writing performances. Our image analysis showed high visual similarity between the two character types, with a larger variance among simplified characters; this may allow simplified Chinese readers to interpolate and generalize their skills to traditional characters. Thus, transfer of perceptual expertise may be constrained by both the similarity in feature and the difference in exemplar variance between the categories. Copyright © 2016 Cognitive Science Society, Inc.

  7. Performance Comparison of SVM and ANN for Handwritten Devnagari Character Recognition

    Directory of Open Access Journals (Sweden)

    Sandhya Arora

    2010-05-01

    Full Text Available Classification methods based on learning from examples have been widely applied to character recognition from the 1990s and have brought forth significant improvements of recognition accuracies. This class of methods includes statistical methods, artificial neural networks, support vector machines (SVM, multiple classifier combination, etc. In this paper, we discuss the characteristics of the some classification methods that have been successfully applied to handwritten Devnagari character recognition and results of SVM and ANNs classification method, applied on Handwritten Devnagari characters. After preprocessing the character image, we extracted shadow features, chain code histogram features, view based features and longest run features. These features are then fed to Neural classifier and in support vector machine for classification. In neural classifier, we explored three ways of combining decisions of four MLP's, designed for four different features.

  8. Performance Comparison of SVM and ANN for Handwritten Devnagari Character Recognition

    CERN Document Server

    Arora, Sandhya; Nasipuri, Mita; Malik, L; Kundu, M; Basu, D K

    2010-01-01

    Classification methods based on learning from examples have been widely applied to character recognition from the 1990s and have brought forth significant improvements of recognition accuracies. This class of methods includes statistical methods, artificial neural networks, support vector machines (SVM), multiple classifier combination, etc. In this paper, we discuss the characteristics of the some classification methods that have been successfully applied to handwritten Devnagari character recognition and results of SVM and ANNs classification method, applied on Handwritten Devnagari characters. After preprocessing the character image, we extracted shadow features, chain code histogram features, view based features and longest run features. These features are then fed to Neural classifier and in support vector machine for classification. In neural classifier, we explored three ways of combining decisions of four MLP's designed for four different features.

  9. Multiple Classifier Combination for Off-line Handwritten Devnagari Character Recognition

    CERN Document Server

    Arora, Sandhya; Nasipuri, Mita; Basu, Dipak Kumar; Kundu, Mahantapas

    2010-01-01

    This work presents the application of weighted majority voting technique for combination of classification decision obtained from three Multi_Layer Perceptron(MLP) based classifiers for Recognition of Handwritten Devnagari characters using three different feature sets. The features used are intersection, shadow feature and chain code histogram features. Shadow features are computed globally for character image while intersection features and chain code histogram features are computed by dividing the character image into different segments. On experimentation with a dataset of 4900 samples the overall recognition rate observed is 92.16% as we considered top five choices results. This method is compared with other recent methods for Handwritten Devnagari Character Recognition and it has been observed that this approach has better success rate than other methods.

  10. Research on Method of Character Recognition Based on Hough Transform and RBF Neural Network

    Directory of Open Access Journals (Sweden)

    Zhang Yin

    2015-01-01

    Full Text Available A method of character recognition based on Hough transform and RBF neural network is proposed through research on weight accumulation algorithm of Hough transform. According to the feature of characters’ structure by using the duality of point-line Hough transform was done. In this method, the number of the points on the same line in parameter space and the position coordinates of the elements in image mapping space were taken to RBF neural network recognition system as characteristic input vector. It reduced the dimension of character feature vector and reflected the overall distribution of character lattice and the essential feature of character shape. The simulation results indicated there were some merits in this improved method: capability of recognition is strong, the quantity of calculation is small, and the speed of calculation is quick.

  11. Effect of Pixel’s Spatial Characteristics on Recognition of Isolated Pixelized Chinese Character

    Science.gov (United States)

    Yang, Kun; Liu, Shuang; Wang, Hong; Liu, Wei; Wu, Yaowei

    2015-01-01

    The influence of pixel’s spatial characteristics on recognition of isolated Chinese character was investigated using simulated prosthestic vision. The accuracy of Chinese character recognition with 4 kinds of pixel number (6*6, 8*8, 10*10, and 12*12 pixel array) and 3 kinds of pixel shape (Square, Dot and Gaussian) and different pixel spacing were tested through head-mounted display (HMD). A captured image of Chinese characters in font style of Hei were pixelized with Square, Dot and Gaussian pixel. Results showed that pixel number was the most important factor which could affect the recognition of isolated pixelized Chinese Chartars and the accuracy of recognition increased with the addition of pixel number. 10*10 pixel array could provide enough information for people to recognize an isolated Chinese character. At low resolution (6*6 and 8*8 pixel array), there were little difference of recognition accuracy between different pixel shape and different pixel spacing. While as for high resolution (10*10 and 12*12 pixel array), the fluctuation of pixel shape and pixel spacing could not affect the performance of recognition of isolated pixelized Chinese Character. PMID:26628934

  12. Effect of Pixel's Spatial Characteristics on Recognition of Isolated Pixelized Chinese Character.

    Science.gov (United States)

    Yang, Kun; Liu, Shuang; Wang, Hong; Liu, Wei; Wu, Yaowei

    2015-01-01

    The influence of pixel's spatial characteristics on recognition of isolated Chinese character was investigated using simulated prosthestic vision. The accuracy of Chinese character recognition with 4 kinds of pixel number (6*6, 8*8, 10*10, and 12*12 pixel array) and 3 kinds of pixel shape (Square, Dot and Gaussian) and different pixel spacing were tested through head-mounted display (HMD). A captured image of Chinese characters in font style of Hei were pixelized with Square, Dot and Gaussian pixel. Results showed that pixel number was the most important factor which could affect the recognition of isolated pixelized Chinese Chartars and the accuracy of recognition increased with the addition of pixel number. 10*10 pixel array could provide enough information for people to recognize an isolated Chinese character. At low resolution (6*6 and 8*8 pixel array), there were little difference of recognition accuracy between different pixel shape and different pixel spacing. While as for high resolution (10*10 and 12*12 pixel array), the fluctuation of pixel shape and pixel spacing could not affect the performance of recognition of isolated pixelized Chinese Character.

  13. Syllable language models for Mandarin speech recognition: exploiting character language models.

    Science.gov (United States)

    Liu, Xunying; Hieronymus, James L; Gales, Mark J F; Woodland, Philip C

    2013-01-01

    Mandarin Chinese is based on characters which are syllabic in nature and morphological in meaning. All spoken languages have syllabiotactic rules which govern the construction of syllables and their allowed sequences. These constraints are not as restrictive as those learned from word sequences, but they can provide additional useful linguistic information. Hence, it is possible to improve speech recognition performance by appropriately combining these two types of constraints. For the Chinese language considered in this paper, character level language models (LMs) can be used as a first level approximation to allowed syllable sequences. To test this idea, word and character level n-gram LMs were trained on 2.8 billion words (equivalent to 4.3 billion characters) of texts from a wide collection of text sources. Both hypothesis and model based combination techniques were investigated to combine word and character level LMs. Significant character error rate reductions up to 7.3% relative were obtained on a state-of-the-art Mandarin Chinese broadcast audio recognition task using an adapted history dependent multi-level LM that performs a log-linearly combination of character and word level LMs. This supports the hypothesis that character or syllable sequence models are useful for improving Mandarin speech recognition performance.

  14. ACCURACY IMPROVEMENT OF HANDWRITTEN CHARACTER RECOGNITION BY GLVQ

    NARCIS (Netherlands)

    Fukumoto, T.; Wakabayashi, T.; Kimura, F.; Miyake, Y.

    2004-01-01

    This paper describes tree­based classification of character images, comparing two methods of tree formation and two methods of matching: nearest neighbor and nearest centroid. The first method, Preprocess Using Relative Distances (PURD) is a tree­based reorganization of a flat list of patterns,

  15. Beginning Students' Perceptions of Effective Activities for Chinese Character Recognition

    Science.gov (United States)

    Wang, Jing; Leland, Christine H.

    2011-01-01

    This study investigates what beginning learners of Chinese perceive as helpful in learning to recognize characters. Thirteen English-speaking participants in a beginning Chinese class answered journal questions and completed a survey over one semester at a large Midwestern university. Findings suggest that participants perceived the usefulness of…

  16. Age of acquisition affects early orthographic processing during Chinese character recognition.

    Science.gov (United States)

    Chen, Baoguo; Dent, Kevin; You, Wenping; Wu, Guolai

    2009-03-01

    Three experiments investigated age of acquisition (AoA) effects on early orthographic processing during Chinese character recognition. In Experiment 1, we measured the accuracy of identification of brief masked characters, accuracy was higher for early compared to late acquired characters. In Experiment 2, the visual duration threshold (VDT) was measured for both early and late acquired Chinese characters. The results showed that early acquired characters were successfully identified at shorter display durations than late acquired characters. Significant AoA effects were also found in Experiment 3, using a lexical decision task requiring mainly orthographic processing (discriminating real Chinese characters from orthographically illegal and unpronounceable characters). In summary, three experiments provide converging empirical evidence, for AoA effects on the early orthographic processing stages of Chinese character recognition. These results suggest that AoA effects during word identification go beyond the phonological or semantic processing stages. These results aslo provide cross-linguistic evidence for an AoA effect on early perceptual processing during identification.

  17. A TMS examination of semantic radical combinability effects in Chinese character recognition.

    Science.gov (United States)

    Hsiao, Janet Hui-Wen; Shillcock, Richard; Lavidor, Michal

    2006-03-17

    The proposal of human foveal splitting assumes a vertical meridian split in the foveal representation and the consequent contralateral projection of information in the two hemifields to the two hemispheres and has been shown to have important implications for visual word recognition. According to this assumption, in Chinese character recognition, the two halves of a centrally fixated character may be initially projected to and processed in different hemispheres. Here, we describe a repetitive transcranial magnetic stimulation (rTMS) investigation of hemispheric processing in Chinese character recognition, through examining semantic radical combinability effects in a character semantic judgment task. The materials used were a dominant type of Chinese character which consists of a semantic radical on the left and a phonetic radical on the right. Thus, according to the split fovea assumption, the semantic and phonetic radicals are initially projected to and processed in the right hemisphere and the left hemisphere, respectively. We show that rTMS over the left occipital cortex impaired the facilitation of semantic radicals with large combinability, whereas right occipital rTMS did not. This interaction between stimulation site and radical combinability reveals a flexible division of labor between the hemispheres in Chinese character recognition, with each hemisphere responding optimally to the information in the contralateral visual hemifield to which it has direct access. The results are also consistent with the split fovea claim, suggesting functional foveal splitting as a universal processing constraint in reading.

  18. Inhibitory stroke neighbour priming in character recognition and reading in Chinese.

    Science.gov (United States)

    Wang, Jingxin; Tian, Jing; Han, Weijin; Liversedge, Simon P; Paterson, Kevin B

    2014-01-01

    In alphabetic languages, prior exposure to a target word's orthographic neighbour influences word recognition in masked priming experiments and the process of word identification that occurs during normal reading. We investigated whether similar neighbour priming effects are observed in Chinese in 4 masked priming experiments (employing a forward mask and 33-ms, 50-ms, and 67-ms prime durations) and in an experiment that measured eye movements while reading. In these experiments, the stroke neighbour of a Chinese character was defined as any character that differed by the addition, deletion, or substitution of one or two strokes. Prime characters were either stroke neighbours or stroke non-neighbours of the target character, and each prime character had either a higher or a lower frequency of occurrence in the language than its corresponding target character. Frequency effects were observed in all experiments, demonstrating that the manipulation of character frequency was successful. In addition, a robust inhibitory priming effect was observed in response times for target characters in the masked priming experiments and in eye fixation durations for target characters in the reading experiment. This stroke neighbour priming was not modulated by the relative frequency of the prime and target characters. The present findings therefore provide a novel demonstration that inhibitory neighbour priming shown previously for alphabetic languages is also observed for nonalphabetic languages, and that neighbour priming (based on stroke overlap) occurs at the level of the character in Chinese.

  19. Two-tier architecture for unconstrained handwritten character recognition

    Indian Academy of Sciences (India)

    K V Prema; N V Subba Reddy

    2002-10-01

    In this paper, we propose an approach that combines the unsupervised and supervised learning techniques for unconstrained handwritten numeral recognition. This approach uses the Kohonen self-organizing neural network for data classification in the first stage and the learning vector quantization (LVQ) model in the second stage to improve classification accuracy. The combined architecture performs better than the Kohonen self-organizing map alone. In the proposed approach, the collection of centroids at different phases of training plays a vital role in the performance of the recognition system. Four experiments have been conducted and experimental results show that the collection of centroids in the middle of the training gives high performance in terms of speed and accuracy. The systems developed also resolve the confusion between handwritten numerals.

  20. Word Type Frequency Alone Can Modulate Hemispheric Asymmetry in Visual Word Recognition: Evidence from Modeling Chinese Character Recognition

    Directory of Open Access Journals (Sweden)

    Janet H. Hsiao

    2011-05-01

    Full Text Available In Chinese orthography, a dominant structure exists in which a semantic radical appears on the left and a phonetic radical on the right (SP characters; the minority, opposite arrangement also exists (PS characters. Recent studies showed that SP character processing is more left hemisphere (LH lateralized than PS character processing; nevertheless, it remains unclear whether this is due to phonetic radical position or character type frequency. Through computational modeling with artificial lexicons, in which we implement a theory of hemispheric asymmetry in perception that posits differential frequency bias in the two hemispheres (i.e., the DFF theory; Ivry & Robertson, 1998, but do not assume phonological processing being LH lateralized, we show that although phonetic radical position, visual complexity of the radicals, and character information structure may all modulate lateralization effects, the difference in character type frequency alone is sufficient to exhibit the effect that the dominant type has a stronger LH lateralization than the minority type. Further analysis suggests that this effect is due to higher visual similarity among characters in the dominant type as compared with those in the minority type. This result demonstrates that word type frequency alone can modulate hemispheric lateralization effects in visual word recognition.

  1. Word Type Frequency Alone Can Modulate Hemispheric Asymmetry in Visual Word Recognition: Evidence from Modeling Chinese Character Recognition

    Science.gov (United States)

    Hsiao, Janet H.; Cheung, Kit

    2011-01-01

    In Chinese orthography, a dominant structure exists in which a semantic radical appears on the left and a phonetic radical on the right (SP characters); the minority, opposite arrangement also exists (PS characters). Recent studies showed that SP character processing is more left hemisphere (LH) lateralized than PS character processing; nevertheless, it remains unclear whether this is due to phonetic radical position or character type frequency. Through computational modeling with artificial lexicons, in which we implement a theory of hemispheric asymmetry in perception that posits differential frequency bias in the two hemispheres (i.e., the DFF theory; Ivry & Robertson, 1998), but do not assume phonological processing being LH lateralized, we show that although phonetic radical position, visual complexity of the radicals, and character information structure may all modulate lateralization effects, the difference in character type frequency alone is sufficient to exhibit the effect that the dominant type has a stronger LH lateralization than the minority type. Further analysis suggests that this effect is due to higher visual similarity among characters in the dominant type as compared with those in the minority type. This result demonstrates that word type frequency alone can modulate hemispheric lateralization effects in visual word recognition.

  2. Russian Character Recognition using Self-Organizing Map

    Science.gov (United States)

    Gunawan, D.; Arisandi, D.; Ginting, F. M.; Rahmat, R. F.; Amalia, A.

    2017-01-01

    The World Tourism Organization (UNWTO) in 2014 released that there are 28 million visitors who visit Russia. Most of the visitors might have problem in typing Russian word when using digital dictionary. This is caused by the letters, called Cyrillic that used by the Russian and the countries around it, have different shape than Latin letters. The visitors might not familiar with Cyrillic. This research proposes an alternative way to input the Cyrillic words. Instead of typing the Cyrillic words directly, camera can be used to capture image of the words as input. The captured image is cropped, then several pre-processing steps are applied such as noise filtering, binary image processing, segmentation and thinning. Next, the feature extraction process is applied to the image. Cyrillic letters recognition in the image is done by utilizing Self-Organizing Map (SOM) algorithm. SOM successfully recognizes 89.09% Cyrillic letters from the computer-generated images. On the other hand, SOM successfully recognizes 88.89% Cyrillic letters from the image captured by the smartphone’s camera. For the word recognition, SOM successfully recognized 292 words and partially recognized 58 words from the image captured by the smartphone’s camera. Therefore, the accuracy of the word recognition using SOM is 83.42%

  3. Recognition of Similar Shaped Handwritten Marathi Characters Using Artificial Neural Network

    Science.gov (United States)

    Jane, Archana P.; Pund, Mukesh A.

    2012-03-01

    The growing need have handwritten Marathi character recognition in Indian offices such as passport, railways etc has made it vital area of a research. Similar shape characters are more prone to misclassification. In this paper a novel method is provided to recognize handwritten Marathi characters based on their features extraction and adaptive smoothing technique. Feature selections methods avoid unnecessary patterns in an image whereas adaptive smoothing technique form smooth shape of charecters.Combination of both these approaches leads to the better results. Previous study shows that, no one technique achieves 100% accuracy in handwritten character recognition area. This approach of combining both adaptive smoothing & feature extraction gives better results (approximately 75-100) and expected outcomes.

  4. Optical Pattern Recognition for Missile Guidance.

    Science.gov (United States)

    1982-11-15

    Cutrona et al., IRE Trans. Inform. Theory, vol. IT-6, p. 386,1960, diodes whose outputs are the elements of W. Each LED is and D. Hecht , Proc. Soc...34, Acta optica Sinica, 1, 401-410, September 1981 (Casasent et al). 35. "Eigenvector Determination by Iterative Optical Methods", Applied optics, 20...Elements and Architectures" (Master’s expected in 1983). 10. Eugene Pochapsky, "Digital Preprocessing and Simulation for Optical Pattern Recognition

  5. Comparison of crisp and fuzzy character networks in handwritten word recognition

    Science.gov (United States)

    Gader, Paul; Mohamed, Magdi; Chiang, Jung-Hsien

    1992-01-01

    Experiments involving handwritten word recognition on words taken from images of handwritten address blocks from the United States Postal Service mailstream are described. The word recognition algorithm relies on the use of neural networks at the character level. The neural networks are trained using crisp and fuzzy desired outputs. The fuzzy outputs were defined using a fuzzy k-nearest neighbor algorithm. The crisp networks slightly outperformed the fuzzy networks at the character level but the fuzzy networks outperformed the crisp networks at the word level.

  6. Recognition of online handwritten Gurmukhi characters based on zone and stroke identification

    Indian Academy of Sciences (India)

    KARUN VERMA; R K SHARMA

    2017-05-01

    Handwriting recognition is a technique that converts handwritten characters into a machine-processable format. Handwritten characters can either be presented to machine online or offline. A good amount of research in this area has been carried out for English, Chinese, Japanese and Korean languages. Research is also going on for Indian languages on developing online handwriting recognition systems. Headline and baseline are common features in most Indic languages which divide a character into three zones, namely, upper, middle andlower zones. Identification of headline and baseline is a major task for classification of strokes located in these three zones. A zone identification algorithm is proposed and tested in this text for online handwriting recognitionof Gurmukhi script. The strokes are grouped into these separate zones and are recognized based on respective support vector machine model for each zone. A rule-based approach has also been applied and tested for generation of characters from the set of recognized strokes. In this work, an accuracy of 95.3% has been achieved for zone identification and an accuracy of 74.8% has been achieved for character identification for Gurmukhi script. This accuracy has been achieved when the recognition engines of three zones were tested onthe dataset of 428 characters each written by 10 users.

  7. The evolution of species recognition in competitive and mating contexts: the relative efficacy of alternative mechanisms of character displacement.

    Science.gov (United States)

    Okamoto, Kenichi W; Grether, Gregory F

    2013-05-01

    Sympatric divergence in traits affecting species recognition can result from selection against cross-species mating (reproductive character displacement, RCD) or interspecific aggression (agonistic character displacement, ACD). When the same traits are used for species recognition in both contexts, empirically disentangling the relative contributions of RCD and ACD to observed character shifts may be impossible. Here, we develop a theoretical framework for partitioning the effects of these processes. We show that when both mate and competitor recognition depend on the same trait, RCD sets the pace of character shifts. Moreover, RCD can cause divergence in competitor recognition, but ACD cannot cause divergence in mate recognition. This asymmetry arises because males with divergent recognition traits may avoid needless interspecific conflicts, but suffer reduced attractiveness to conspecific females. Therefore, the key empirical issue is whether the same or different traits are used for mate recognition and competitor recognition. © 2013 Blackwell Publishing Ltd/CNRS.

  8. Pattern Association For Character Recognition By Back-Propagation Algorithm Using Neural Network Approach

    Directory of Open Access Journals (Sweden)

    S.P.Kosbatwar

    2012-03-01

    Full Text Available The use of artificial neural network in applications can dramatically simplify the code and improve quality of recognition while achieving good performance. Another benefit of using neural network in application is extensibility of the system – ability to recognize more character sets than initially defined. Most of traditional systems are not extensible enough. In this paper recognition ofcharacters is possible by using neural network back propagation algorithm.

  9. Interspecific aggression and character displacement of competitor recognition in Hetaerina damselflies.

    Science.gov (United States)

    Anderson, Christopher N; Grether, Gregory F

    2010-02-22

    In zones of sympatry between closely related species, species recognition errors in a competitive context can cause character displacement in agonistic signals and competitor recognition functions, just as species recognition errors in a mating context can cause character displacement in mating signals and mate recognition. These two processes are difficult to distinguish because the same traits can serve as both agonistic and mating signals. One solution is to test for sympatric shifts in recognition functions. We studied competitor recognition in Hetaerina damselflies by challenging territory holders with live tethered conspecific and heterospecific intruders. Heterospecific intruders elicited less aggression than conspecific intruders in species pairs with dissimilar wing coloration (H. occisa/H. titia, H. americana/H. titia) but not in species pairs with similar wing coloration (H. occisa/H. cruentata, H. americana/H. cruentata). Natural variation in the area of black wing pigmentation on H. titia intruders correlated negatively with heterospecific aggression. To directly examine the role of wing coloration, we blackened the wings of H. occisa or H. americana intruders and measured responses of conspecific territory holders. This treatment reduced territorial aggression at multiple sites where H. titia is present, but not at allopatric sites. These results provide strong evidence for agonistic character displacement.

  10. The Influence of Writing Experiences on Holistic Processing in Chinese Character Recognition

    Science.gov (United States)

    Tso, Ricky Van Yip; Au, Terry Kit-Fong; Hsiao, Janet Hui-Wen

    2011-01-01

    Holistic processing has been shown to be a behavioral marker of face recognition and object recognition in experts. In contrast, Hsiao and Cottrell (2009) showed that reduced holistic processing is a marker of visual expertise in Chinese character recognition. Here we tested Chinese-literates who can read and write Chinese characters (Writers) and literates whose reading performance far exceeded their writing ability (Limited-writers). We found that Writers perceived Chinese characters less holistically than Limited-writers. In addition to Hsiao and Cottrell's (2009) findings, our study further showed that such reduction in holistic processing can be explained by writing experience in Chinese. This result may be because Chinese Writers exhibit a better awareness of the orthographic components of Chinese characters than Limited-writers due to their writing experience. This study also showed that Limited-writers are better at recognizing a character embedded in a word of a familiar font than when it is alone or of an unfamiliar font, suggesting that their reading performances depend on both the context and font familiarity. This study is also the first to report on the Chinese reading population that has far poorer writing performance than reading performance.

  11. The Influence of Writing Experiences on Holistic Processing in Chinese Character Recognition

    Directory of Open Access Journals (Sweden)

    Ricky Van Yip Tso

    2011-05-01

    Full Text Available Holistic processing has been shown to be a behavioral marker of face recognition and object recognition in experts. In contrast, Hsiao and Cottrell (2009 showed that reduced holistic processing is a marker of visual expertise in Chinese character recognition. Here we tested Chinese-literates who can read and write Chinese characters (Writers and literates whose reading performance far exceeded their writing ability (Limited-writers. We found that Writers perceived Chinese characters less holistically than Limited-writers. In addition to Hsiao and Cottrell's (2009 findings, our study further showed that such reduction in holistic processing can be explained by writing experience in Chinese. This result may be because Chinese Writers exhibit a better awareness of the orthographic components of Chinese characters than Limited-writers due to their writing experience. This study also showed that Limited-writers are better at recognizing a character embedded in a word of a familiar font than when it is alone or of an unfamiliar font, suggesting that their reading performances depend on both the context and font familiarity. This study is also the first to report on the Chinese reading population that has far poorer writing performance than reading performance.

  12. Chinese Children's Character Recognition: Visuo-Orthographic, Phonological Processing and Morphological Skills

    Science.gov (United States)

    Li, Hong; Shu, Hua; McBride-Chang, Catherine; Liu, Hongyun; Peng, Hong

    2012-01-01

    Tasks tapping visual skills, orthographic knowledge, phonological awareness, speeded naming, morphological awareness and Chinese character recognition were administered to 184 kindergarteners and 273 primary school students from Beijing. Regression analyses indicated that only syllable deletion, morphological construction and speeded number naming…

  13. Fuzzy-based multi-kernel spherical support vector machine for effective handwritten character recognition

    Indian Academy of Sciences (India)

    A K SAMPATH; N GOMATHI

    2017-09-01

    Due to constant advancement of computer tools, automated conversion of images of typed,handwritten and printed text is important for various applications, which has led to intense research for several years in the field of offline handwritten character recognition. Handwritten character recognition is complex because characters differ by writing style, shapes and writing devices. To resolve this problem, we propose a fuzzy-based multi-kernel spherical support vector machine. Initially, the input image is fed into the pre-processing step to acquire suitable images. Then, histogram of oriented gradient (HOG) descriptor is utilised forfeature extraction. The HOG descriptor constitutes a histogram estimation and normalisation computation. The features are then classified using the proposed classifier for character recognition. In the proposed classifier, we design a new multi-kernel function based on the fuzzy triangular membership function. Finally, a newly developed multi-kernel function is incorporated into the spherical support vector machine to enhance the performance significantly. The experimental results are evaluated and performance is analysed by metrics such as false acceptance rate, false rejection rate and accuracy, which is implemented in MATLAB. Then, the performance is compared with existing systems based on the percentage of training data samples. Thus, the outcome of our proposed system attains 99% higher accuracy, which ensures efficient recognition performance

  14. Fast character projection electron beam lithography for diffractive optical elements

    Science.gov (United States)

    Harzendorf, Torsten; Fuchs, Frank; Banasch, Michael; Zeitner, Uwe D.

    2014-05-01

    Electron beam lithography becomes attractive also for the fabrication of large scale diffractive optical elements by the use of the character projection (CP) technique. Even in the comparable fast variable shaped beam (VSB) exposure approach for conventional electron beam writers optical nanostructures may require very long writing times exceeding 24 hours per wafer because of the high density of features, as required by e.g. sub-wavelength nanostructures. Using character projection, the writing time can be reduced by more than one order of magnitude, due to the simultaneous exposure of multiple features. The benefit of character projection increases with increasing complexity of the features and decreasing period. In this contribution we demonstrate the CP technique for a grating of hexagonal symmetry at 350nm period. The pattern is designed to provide antireflective (AR) properties, which can be adapted in their spectral and angular domain for applications from VIS to NIR by changing the feature size and the etching depth of the nanostructure. This AR nanostructure can be used on the backside of optical elements e.g. gratings, when an AR coating stack could not be applied for the reason of climatic conditions or wave front accuracy.

  15. Handwritten Character Recognition Based on the Specificity and the Singularity of the Arabic Language

    Directory of Open Access Journals (Sweden)

    Youssef Boulid

    2017-08-01

    Full Text Available A good Arabic handwritten recognition system must consider the characteristics of Arabic letters which can be explicit such as the presence of diacritics or implicit such as the baseline information (a virtual line on which cursive text are aligned and/join. In order to find an adequate method of features extraction, we have taken into consideration the nature of the Arabic characters. The paper investigate two methods based on two different visions: one describes the image in terms of the distribution of pixels, and the other describes it in terms of local patterns. Spatial Distribution of Pixels (SDP is used according to the first vision; whereas Local Binary Patterns (LBP are used for the second one. Tested on the Arabic portion of the Isolated Farsi Handwritten Character Database (IFHCDB and using neural networks as a classifier, SDP achieve a recognition rate around 94% while LBP achieve a recognition rate of about 96%.

  16. 26 CFR 1.741-1 - Recognition and character of gain or loss on sale or exchange.

    Science.gov (United States)

    2010-04-01

    ... 26 Internal Revenue 8 2010-04-01 2010-04-01 false Recognition and character of gain or loss on sale or exchange. 1.741-1 Section 1.741-1 Internal Revenue INTERNAL REVENUE SERVICE, DEPARTMENT OF THE... Recognition and character of gain or loss on sale or exchange. (a) The sale or exchange of an interest in...

  17. A comparative study of local descriptors for Arabic character recognition on mobile devices

    Science.gov (United States)

    Tounsi, Maroua; Moalla, Ikram; Alimi, Adel M.; Lebourgeois, Franck

    2015-02-01

    Nowadays, the number of mobile applications based on image registration and recognition is increasing. Most interesting applications include mobile translator which can read text characters in the real world and translates it into the native language instantaneously. In this context, we aim to recognize characters in natural scenes by computing significant points so called key points or features/interest points in the image. So, it will be important to compare and evaluate features descriptors in terms of matching accuracy and processing time in a particular context of natural scene images. In this paper, we were interested on comparing the efficiency of the binary features as alternatives to the traditional SIFT and SURF in matching Arabic characters descended from natural scenes. We demonstrate that the binary descriptor ORB yields not only to similar results in terms of matching characters performance that the famous SIFT but also to faster computation suitable for mobile applications.

  18. The role of lexical variables in the visual recognition of Chinese characters: A megastudy analysis.

    Science.gov (United States)

    Sze, Wei Ping; Yap, Melvin J; Rickard Liow, Susan J

    2015-01-01

    Logographic Chinese orthography partially represents both phonology and semantics. By capturing the online processing of a large pool of Chinese characters, we were able to examine the relative salience of specific lexical variables when this nonalphabetic script is read. Using a sample of native mainland Chinese speakers (N = 35), lexical decision latencies for 1560 single characters were collated into a database, before the effects of a comprehensive range of variables were explored. Hierarchical regression analyses determined the unique item-level variance explained by orthographic (frequency, stroke count), semantic (age of learning, imageability, number of meanings), and phonological (consistency, phonological frequency) factors. Orthographic and semantic variables, respectively, accounted for more collective variance than the phonological variables. Significant main effects were further observed for the individual orthographic and semantic predictors. These results are consistent with the idea that skilled readers tend to rely on orthographic and semantic information when processing visually presented characters. This megastudy approach marks an important extension to existing work on Chinese character recognition, which hitherto has relied on factorial designs. Collectively, the findings reported here represent a useful set of empirical constraints for future computational models of character recognition.

  19. The modulation of semantic transparency on the recognition memory for two-character Chinese words.

    Science.gov (United States)

    Han, Yi-Jhong; Huang, Shuo-Chieh; Lee, Chia-Ying; Kuo, Wen-Jui; Cheng, Shih-Kuen

    2014-11-01

    This study demonstrated that semantic transparency as a linguistic property modulates the recognition memory for two-character Chinese words, with opaque words (i.e., words whose meanings cannot be derived from constituent characters-e.g., "[/guang/, light][/gun/, stick]", bachelor) remembered better than transparent words (i.e., words whose meanings can be derived from constituent characters-e.g., "[/cha/, tea][/bei/, cup]", teacup). In Experiment 1, the participants made lexical decisions on transparent words, opaque words, and nonwords in the study and then engaged in an old/new recognition test. Experiment 2 employed a concreteness judgment as the encoding task to ensure equivalent semantic processing for opaque and transparent words. In Experiment 3, the neighborhood size of the two-character words was manipulated together with their semantic transparency. In all three experiments, opaque words were found to be better remembered than transparent words. We concluded that the conceptual incongruence between the meanings of a whole word and its constituent characters made opaque words more distinctive and, hence, better remembered than transparent words.

  20. P2-36: Spatial Frequency Characteristics of Chinese Character Recognition in Different Complexity Categories

    Directory of Open Access Journals (Sweden)

    On-Ting Lo

    2012-10-01

    Full Text Available Objective: Human visual system is able to recognize objects in large complexity variation. Despite such capability, little is known about the effects of complexity on object recognition. Here we studied the spatial frequency (SF characteristics in identifying Chinese characters (CCs of different complexity levels. Method: Stimuli were 150 frequently used CCs categorized into 3 complexity groups. Each character was digitally band-passed by 11 cosine log filters (bandwidth = 2 octaves, center frequency = 1.27 to 12.8 cycles/character in 0.1 log step. We measured contrast sensitivity for recognizing CCs of sizes 0.5°, 1°, and 2°. Peak SF (cycles/deg and bandwidth (octaves were plotted against character size in nominal character frequency (cycles/deg. A CSF ideal observer model (Chung et al., 2002 Vision Research 42 2137–2152 was formulated to examine whether early CSF filtering followed by template matching could explain human performance. Results: Log-log slopes of peak SF vs. size functions were 0.60±0.04 (M±SD, 0.67±0.02, and 0.72±0.05 for the low, medium, and high complexity groups. Bandwidth of the tuning functions was approximately 2 octaves for all complexity groups. Preliminary results from the CSF ideal observer analysis showed shallower slopes for the peak SF vs. size functions, but a similar trend for the bandwidth data compared with human performance. Conclusions: Peak SF of the tuning function did not scale perfectly with character size (log-log slopes < 1. The SF characteristics of CC recognition exhibited size-dependence, which differed across complexity groups. The ideal observer model utilizing human CSF and character-identity information failed to explain our data.

  1. Classification Of Gradient Change Features Using MLP For Handwritten Character Recognition

    CERN Document Server

    Arora, Sandhya; Bhattacharjee, Debotosh; Nasipuri, Mita

    2010-01-01

    A novel, generic scheme for off-line handwritten English alphabets character images is proposed. The advantage of the technique is that it can be applied in a generic manner to different applications and is expected to perform better in uncertain and noisy environments. The recognition scheme is using a multilayer perceptron(MLP) neural networks. The system was trained and tested on a database of 300 samples of handwritten characters. For improved generalization and to avoid overtraining, the whole available dataset has been divided into two subsets: training set and test set. We achieved 99.10% and 94.15% correct recognition rates on training and test sets respectively. The purposed scheme is robust with respect to various writing styles and size as well as presence of considerable noise.

  2. Improving the character recognition efficiency of feed forward BP neural network

    CERN Document Server

    Choudhary, Amit

    2011-01-01

    This work is focused on improving the character recognition capability of feed-forward back-propagation neural network by using one, two and three hidden layers and the modified additional momentum term. 182 English letters were collected for this work and the equivalent binary matrix form of these characters was applied to the neural network as training patterns. While the network was getting trained, the connection weights were modified at each epoch of learning. For each training sample, the error surface was examined for minima by computing the gradient descent. We started the experiment by using one hidden layer and the number of hidden layers was increased up to three and it has been observed that accuracy of the network was increased with low mean square error but at the cost of training time. The recognition accuracy was improved further when modified additional momentum term was used.

  3. The modulation of stimulus structure on visual field asymmetry effects: the case of Chinese character recognition.

    Science.gov (United States)

    Hsiao, Janet H; Cheng, Liao

    2013-09-01

    Recent research suggests that visual field (VF) asymmetry effects in visual recognition may be influenced by information distribution within the stimuli for the recognition task in addition to hemispheric processing differences: Stimuli with more information on the left have a right VF (RVF) advantage because the left part is closer to the centre, where the highest visual acuity is obtained. It remains unclear whether visual complexity distribution of the stimuli also has similar modulation effects. Here we used Chinese characters with contrasting structures-left-heavy, symmetric, and right-heavy, in terms of either visual complexity of components or information distribution defined by location of the phonetic component-and examined participants' naming performance. We found that left-heavy characters had the largest RVF advantage, followed by symmetric and right-heavy characters; this effect was only observed in characters that contrasted in information distribution, in which information for pronunciation was skewed to the phonetic component, but not in those that contrasted only in visual complexity distribution and had no phonetic component. This result provides strong evidence for the influence of information distribution within the stimuli on VF asymmetry effects; in contrast, visual complexity distribution within the stimuli does not have similar modulation effects.

  4. A novel handwritten character recognition system using gradient based features and run length count

    Indian Academy of Sciences (India)

    G Raju; Bindu S Moni; Madhu S Nair

    2014-12-01

    In this paper, we propose a novel hand written character recognition systemusing a combination of gradient-based features and run length count (GBF–RLC). The performance of the proposed method has been tested on Malayalam script, a South Indian language. The gradient of image is the intensity at each point, giving the direction of the largest possible increase from light to dark and the rate of change in that direction. RLC is the count of contiguous group of 1’s encountered in a left to right/top to bottom scan of a character image or block of an image. Classification was carried out with a Simplified Quadratic Classifier (SQDF) and Multi Layer Perceptron (MLP). A database containing 19,800 isolated handwritten characters pertaining to 44 classes was used for the study. The feature vector is augmented by including aspect ratio, position of centroid and ratio of pixels on the vertical halves of a character image. The recognition accuracy of 99.78% was achieved with minimum computational and storage requirement.

  5. Scene text recognition in mobile applications by character descriptor and structure configuration.

    Science.gov (United States)

    Yi, Chucai; Tian, Yingli

    2014-07-01

    Text characters and strings in natural scene can provide valuable information for many applications. Extracting text directly from natural scene images or videos is a challenging task because of diverse text patterns and variant background interferences. This paper proposes a method of scene text recognition from detected text regions. In text detection, our previously proposed algorithms are applied to obtain text regions from scene image. First, we design a discriminative character descriptor by combining several state-of-the-art feature detectors and descriptors. Second, we model character structure at each character class by designing stroke configuration maps. Our algorithm design is compatible with the application of scene text extraction in smart mobile devices. An Android-based demo system is developed to show the effectiveness of our proposed method on scene text information extraction from nearby objects. The demo system also provides us some insight into algorithm design and performance improvement of scene text extraction. The evaluation results on benchmark data sets demonstrate that our proposed scheme of text recognition is comparable with the best existing methods.

  6. Neural correlates of familiarity and conceptual fluency in a recognition test with ancient pictographic characters.

    Science.gov (United States)

    Hou, Mingzhu; Safron, Adam; Paller, Ken A; Guo, Chunyan

    2013-06-26

    Familiarity and conceptual priming refer to distinct memory expressions and are subtypes of explicit memory and implicit memory, respectively. Given that the neural events that produce conceptual priming may in some cases promote familiarity, distinguishing between neural signals of these two types of memory may further our understanding of recognition memory mechanisms. Although FN400 event-related potentials observed during recognition tests have often been ascribed to familiarity, much evidence suggests that they should instead be ascribed to conceptual fluency. To help resolve this controversy, we studied potentials elicited by unrecognizable ancient Chinese characters. These stimuli were categorized as high or low in meaningfulness based on subjective ratings. Conceptual priming was produced exclusively by repetition of characters high in meaningfulness. During a recognition test in which recollection was discouraged, FN400 old-new effects were observed, and amplitudes of the FN400 potentials varied inversely with familiarity confidence. However, these effects were absent for old items given low meaningfulness ratings. For both high and low meaningfulness, late positive (LPC) potentials were found in old-new comparisons, and LPC amplitudes were greater when higher familiarity confidence was registered during the recognition test. These findings linked familiarity and conceptual fluency with different brain potentials - LPC and FN400, respectively - and provide additional evidence that explicit memory and implicit memory have distinct neural substrates.

  7. Most probable longest common subsequence for recognition of gesture character input.

    Science.gov (United States)

    Frolova, Darya; Stern, Helman; Berman, Sigal

    2013-06-01

    This paper presents a technique for trajectory classification with applications to dynamic free-air hand gesture recognition. Such gestures are unencumbered and drawn in free air. Our approach is an extension to the longest common subsequence (LCS) classification algorithm. A learning preprocessing stage is performed to create a probabilistic 2-D template for each gesture, which allows taking into account different trajectory distortions with different probabilities. The modified LCS, termed the most probable LCS (MPLCS), is developed to measure the similarity between the probabilistic template and the hand gesture sample. The final decision is based on the length and probability of the extracted subsequence. Validation tests using a cohort of gesture digits from video-based capture show that the approach is promising with a recognition rate of more than 98 % for video stream preisolated digits. The MPLCS algorithm can be integrated into a gesture recognition interface to facilitate gesture character input. This can greatly enhance the usability of such interfaces.

  8. Priming effects in Chinese character recognition for Chinese children with developmental dyslexia

    Institute of Scientific and Technical Information of China (English)

    Yuliang Zou; Jing Wang; Hanrong Wu

    2009-01-01

    BACKGROUND:Dyslexic children exhibit reading ability unmatched to age,although they possess normal intelligence and are well educated.OBJECTIVE:To examine the performance of dyslexic children in Chinese characters visual recognition tasks and to investigate the relationship between priming effect in character recognition and dyslexia.DESIGN,TIME AND SETTING:A case-control study was performed at the Department of Children and Adolescent Health and Maternal Care,School of Public Health,Tongji Medical College,Huazhong University of Science and Technology between March and June 2007.PARTICIPANTS:A total of 75 primary school students in grades 3 and 5 were selected from two primary schools in Wuhan City,Hubei province,China,and were assigned to three groups.(1) Reading disability (RD,n=25);(2) chronological age (CA) group (n=25 normal readers that were intelligence quotient and age-matched to the RD group);(3) reading level (RL) group (n=25 normal readers that were intelligence quotient and RL-matched to the RD group).All children were right-handed and had normal or corrected-to-normal vision.METHODS:Recognition of target characters was performed in each child using a masked prime paradigm.Recognition speed and accuracy of graphic,phonological,and semantic characters were examined.Simultaneously,data,with respect to response time for each target character and error rate,were recorded to calculate facilitation values (unrelated RT-related RT).MAIN OUTCOME MEASURES:Response time,facilitation,and error rate in Chinese character recognition task were calculated.RESULTS:The baseline-adjusted facilitation of graphic,phonological,and semantic priming for dyslexic children was -0.010,-0.010,and 0.001,respectively.Dyslexic children displayed inhibition in graphic and phonological prime conditions.Facilitations under the three prime conditions were 0.026,0.026,and 0.022 for the CA group.In the RL group,results were 0.062,0.058,and 0.031 respectively.The differences of baseline

  9. Neural correlates of foveal splitting in reading: evidence from an ERP study of Chinese character recognition.

    Science.gov (United States)

    Hsiao, Janet Hui-wen; Shillcock, Richard; Lee, Chia-ying

    2007-03-25

    Recent research on foveal structure and reading suggests that the two halves of a centrally fixated word seem to be initially projected to, and processed in, different hemispheres. In the current study, we utilize two contrasting structures in Chinese orthography, "SP" (the semantic radical on the left and the phonetic radical on the right) and "PS" characters (the opposite structure), to examine foveal splitting effects in event-related potential (ERP) recordings. We showed that when participants silently named centrally presented characters, there was a significant interaction between character type and hemisphere in N1 amplitude: SP characters elicited larger N1 compared with PS characters in the left hemisphere, whereas the right hemisphere had the opposite pattern. This effect is consistent with the split fovea claim, suggesting that the two halves of a character may be initially projected to and processed in different hemispheres. There was no such interaction observed in an earlier component P1. Also, there was an interaction between character type and sex of the reader in N350 amplitude. This result is consistent with Hsiao and Shillcock's [Hsiao, J. H., & Shillcock, R. (2005b). Foveal splitting causes differential processing of Chinese orthography in the male and female brain. Cognitive Brain Research, 25, 531-536] behavioural study, which showed a similar interaction in naming response time. They argued that this effect was due to a more left-lateralized network for phonological processing in the male brain compared with the female brain. The results hence showed that foveal splitting effects in visual word recognition were observed in N1 the earliest, and could extend far enough to interact with the sex of the reader as revealed in N350.

  10. An Effect of Noise in Printed Character Recognition System Using Neural Network

    Directory of Open Access Journals (Sweden)

    GHEORGHITA, S.

    2013-02-01

    Full Text Available In this article we present the implementation of a neural network model trained with a high noise level using a backpropagation algorithm and the experimental results for printed character recognition, based on the idea of using the primary information by reorganising it in a different format. The values obtained at the outputs of each network are processed by using analysis algorithms designed for this purpose. The suggested model is made up of two neural networks and two analysis modules. In M1 Module we designed a value analysis algorithm for all the outputs of the two neural networks in order to select the best values provided by the networks. The M2 Module also contains a designed algorithm, which assesses the data based on the fact that the highest values are directly correlated with the probability of correctly identifying the characters entered into the networks. Results are obtained for noise of up to 50% applied to the input data. The values obtained at the outputs of the two modules emphasises the increase of the printed character recognition level up to 89.1% for the M1 module and up to 89.8% for the M2 module, the number of errors decreasing vis-a-vis the RNA2 network response from 12.5% to 10.9%, and 10.2%, respectively. In order to set up the hidden layer of 90 neurons, a value of 92% was obtained at the output of the M2 analysis module.The performed model increased the printed character recognition rate by using the same primary information in a different manner. The validity and functionality of the suggested model are confirmed by experimental results.

  11. Optical correlation recognition based on LCOS

    Science.gov (United States)

    Tang, Mingchuan; Wu, Jianhong

    2013-08-01

    Vander-Lugt correlator[1] plays an important role in optical pattern recognition due to the characteristics of accurate positioning and high signal-to-noise ratio. The ideal Vander-Lugt correlator should have the ability of outputting strong and sharp correlation peak in allusion to the true target, in the existing Spatial Light Modulators[2], Liquid Crystal On Silicon(LCOS) has been the most competitive candidate for the matched filter owing to the continuous phase modulation peculiarity. Allowing for the distortions of the target to be identified including rotations, scaling changes, perspective changes, which can severely impact the correlation recognition results, herein, we present a modified Vander-Lugt correlator based on the LCOS by means of applying an iterative algorithm to the design of the filter so that the correlator can invariant to the distortions while maintaining good performance. The results of numerical simulation demonstrate that the filter could get the similar recognition results for all the training images. And the experiment shows that the modified correlator achieves the 180° rotating tolerance significantly improving the recognition efficiency of the correlator.

  12. Optimizing Chinese character displays improves recognition and reading performance of simulated irregular phosphene maps.

    Science.gov (United States)

    Lu, Yanyu; Kan, Han; Liu, Jie; Wang, Jing; Tao, Chen; Chen, Yao; Ren, Qiushi; Hu, Jie; Chai, Xinyu

    2013-04-26

    A visual prosthesis may elicit an irregular phosphene map relative to a regular electrode array. This study used simulated irregular phosphene maps as a way of optimizing the display methods of Chinese characters (CCs) to improve recognition and reading performance. TWENTY SUBJECTS WITH NORMAL OR CORRECTED SIGHT PARTICIPATED IN TWO EXPERIMENTS (9 FEMALES, 11 MALES, 2030 YEARS OF AGE). EXPERIMENT 1: two character display methods were proposed: selecting phosphenes covered by character strokes on a simulated phosphene array (projection method) and finding the phosphene closest to the expected location in some range of an irregular phosphene array as a substitute (nearest neighbor search [NNS] method). The recognition accuracy of CCs was investigated using six levels for the coverage ratio of stroke and phosphene area and for search range, respectively, for two methods, for several irregularity levels. Experiment 2: reading accuracy (RA) and reading efficiency (RE) were measured using the regular array correspondence and NNS methods. EXPERIMENT 1: projection and NNS methods were significantly affected by coverage ratio or search range. NNS significantly improved CC recognition accuracy to the highest at 81.3 ± 2.7% and 59.1 ± 5.2%, respectively, for different irregularity levels, compared with the projection method. Experiment 2: RA and RE significantly decreased as the distortion level increased; NNS significantly improved RA (from approximately 40% to >80%) and RE (from approximately 13 char/min to >40 char/min) when reading more irregular paragraphs. The performance of CC recognition and paragraph reading when using an irregular phosphene array can be improved through optimizing the display method.

  13. The visual magnocellular-dorsal dysfunction in Chinese children with developmental dyslexia impedes Chinese character recognition.

    Science.gov (United States)

    Zhao, Jing; Qian, Yi; Bi, Hong-Yan; Coltheart, Max

    2014-11-20

    The visual magnocellular-dorsal (M-D) deficit theory of developmental dyslexia (DD) is still highly debated. Many researchers have made great efforts to investigate the relationship between M-D dysfunction and reading disability. Given that visual analysis plays an important role in Chinese reading, the present study tried to examine how the M-D dysfunction affected Chinese character recognition in Chinese children with DD. Sixteen DD children with M-D deficit, fifteen DD children with normal M-D function and twenty-seven age-matched typically developing children participated in this study. A global/local decision task was adopted, in which we manipulated the spatial frequency of target characters to separate an M-D condition from an unfiltered condition. Results of reaction times and error rates showed that in the M-D condition both M-D normal dyslexics and controls exhibited a significant global precedence effect, with faster responses and lower error rates in global decision than in local decision. In contrast, this global advantage was absent for the M-D impaired dyslexics. Accordingly, we propose that the M-D impairment present in some but not all dyslexics might influence global recognition of Chinese characters in this subgroup of children with DD, which might be implicated in their difficulties in learning to read.

  14. Super-resolution Image Created from a Sequence of Images with Application of Character Recognition

    Directory of Open Access Journals (Sweden)

    Leandro Luiz de Almeida

    2013-12-01

    Full Text Available Super-resolution techniques allow combine multiple images of the same scene to obtain an image with increased geometric and radiometric resolution, called super-resolution image. In this image are enhanced features allowing to recover important details and information. The objective of this work is to develop efficient algorithm, robust and automated fusion image frames to obtain a super-resolution image. Image registration is a fundamental step in combining several images that make up the scene. Our research is based on the determination and extraction of characteristics defined by the SIFT and RANSAC algorithms for automatic image registration. We use images containing characters and perform recognition of these characters to validate and show the effectiveness of our proposed method. The distinction of this work is the way to get the matching and merging of images because it occurs dynamically between elements common images that are stored in a dynamic matrix.

  15. Apply lightweight recognition algorithms in optical music recognition

    Science.gov (United States)

    Pham, Viet-Khoi; Nguyen, Hai-Dang; Nguyen-Khac, Tung-Anh; Tran, Minh-Triet

    2015-02-01

    The problems of digitalization and transformation of musical scores into machine-readable format are necessary to be solved since they help people to enjoy music, to learn music, to conserve music sheets, and even to assist music composers. However, the results of existing methods still require improvements for higher accuracy. Therefore, the authors propose lightweight algorithms for Optical Music Recognition to help people to recognize and automatically play musical scores. In our proposal, after removing staff lines and extracting symbols, each music symbol is represented as a grid of identical M ∗ N cells, and the features are extracted and classified with multiple lightweight SVM classifiers. Through experiments, the authors find that the size of 10 ∗ 12 cells yields the highest precision value. Experimental results on the dataset consisting of 4929 music symbols taken from 18 modern music sheets in the Synthetic Score Database show that our proposed method is able to classify printed musical scores with accuracy up to 99.56%.

  16. Kinect Who’s Coming - Applying Kinect to Human Body Height Measurement to Improve Character Recognition Performance

    Directory of Open Access Journals (Sweden)

    Hau-Wei Lee

    2015-05-01

    Full Text Available A great deal of relevant research on character recognition has been carried out, but a certain amount of time is needed to compare faces from a large database. The Kinect is able to obtain three-dimensional coordinates for an object (x & y axes and depth, and in recent years research on its applications has expanded from use in gaming to that of image measurement. This study uses Kinect skeleton information to conduct body height measurements with the aim of improving character recognition performance. Time spent searching and comparing characters is reduced by creating height categories. The margin of error for height used in this investigation was ± 5 cm; therefore, face comparisons were only executed for people in the database within ±5 cm of the body height measured, reducing the search time needed. In addition, using height and facial features simultaneously to conduct character recognition can also reduce the frequency of mistaken recognition. The Kinect was placed on a rotary stage and the position of the head on the body frame was used to conduct body tracking. Body tracking can be used to reduce image distortion caused by the lens of the Kinect. EmguCV was used for image processing and character recognition. The methods proposed in this study can be used in public safety, student attendance registration, commercial VIP recognition and many others.

  17. Robust recognition of degraded machine-printed characters using complementary similarity measure and error-correction learning

    Science.gov (United States)

    Hagita, Norihiro; Sawaki, Minako

    1995-03-01

    Most conventional methods in character recognition extract geometrical features such as stroke direction, connectivity of strokes, etc., and compare them with reference patterns in a stored dictionary. Unfortunately, geometrical features are easily degraded by blurs, stains and the graphical background designs used in Japanese newspaper headlines. This noise must be removed before recognition commences, but no preprocessing method is completely accurate. This paper proposes a method for recognizing degraded characters and characters printed on graphical background designs. This method is based on the binary image feature method and uses binary images as features. A new similarity measure, called the complementary similarity measure, is used as a discriminant function. It compares the similarity and dissimilarity of binary patterns with reference dictionary patterns. Experiments are conducted using the standard character database ETL-2 which consists of machine-printed Kanji, Hiragana, Katakana, alphanumeric, an special characters. The results show that this method is much more robust against noise than the conventional geometrical feature method. It also achieves high recognition rates of over 92% for characters with textured foregrounds, over 98% for characters with textured backgrounds, over 98% for outline fonts, and over 99% for reverse contrast characters.

  18. Visual Similarity of Words Alone Can Modulate Hemispheric Lateralization in Visual Word Recognition: Evidence from Modeling Chinese Character Recognition

    Science.gov (United States)

    Hsiao, Janet H.; Cheung, Kit

    2016-01-01

    In Chinese orthography, the most common character structure consists of a semantic radical on the left and a phonetic radical on the right (SP characters); the minority, opposite arrangement also exists (PS characters). Recent studies showed that SP character processing is more left hemisphere (LH) lateralized than PS character processing.…

  19. Visual Similarity of Words Alone Can Modulate Hemispheric Lateralization in Visual Word Recognition: Evidence from Modeling Chinese Character Recognition

    Science.gov (United States)

    Hsiao, Janet H.; Cheung, Kit

    2016-01-01

    In Chinese orthography, the most common character structure consists of a semantic radical on the left and a phonetic radical on the right (SP characters); the minority, opposite arrangement also exists (PS characters). Recent studies showed that SP character processing is more left hemisphere (LH) lateralized than PS character processing.…

  20. A Bayesian computational model for online character recognition and disability assessment during cursive eye writing.

    Science.gov (United States)

    Diard, Julien; Rynik, Vincent; Lorenceau, Jean

    2013-01-01

    This research involves a novel apparatus, in which the user is presented with an illusion inducing visual stimulus. The user perceives illusory movement that can be followed by the eye, so that smooth pursuit eye movements can be sustained in arbitrary directions. Thus, free-flow trajectories of any shape can be traced. In other words, coupled with an eye-tracking device, this apparatus enables "eye writing," which appears to be an original object of study. We adapt a previous model of reading and writing to this context. We describe a probabilistic model called the Bayesian Action-Perception for Eye On-Line model (BAP-EOL). It encodes probabilistic knowledge about isolated letter trajectories, their size, high-frequency components of the produced trajectory, and pupil diameter. We show how Bayesian inference, in this single model, can be used to solve several tasks, like letter recognition and novelty detection (i.e., recognizing when a presented character is not part of the learned database). We are interested in the potential use of the eye writing apparatus by motor impaired patients: the final task we solve by Bayesian inference is disability assessment (i.e., measuring and tracking the evolution of motor characteristics of produced trajectories). Preliminary experimental results are presented, which illustrate the method, showing the feasibility of character recognition in the context of eye writing. We then show experimentally how a model of the unknown character can be used to detect trajectories that are likely to be new symbols, and how disability assessment can be performed by opportunistically observing characteristics of fine motor control, as letter are being traced. Experimental analyses also help identify specificities of eye writing, as compared to handwriting, and the resulting technical challenges.

  1. Chinese character recognition in mirror reading: evidence from event-related potential.

    Science.gov (United States)

    Zhang, Ye; Qiu, Jiang; Huang, He; Zhang, Qinglin; Bao, Baier

    2009-10-01

    As is well known, mirror reading in language requires recognition of words and letters in mirror-reversed pattern compared with normal reading, and the cognitive mechanism underlying the mirror reading may involve two critical processes: visuospatial transformation and linguistic regulation. Chinese characters, different from English, are characterized by some unique features in orthography and spelling. Using ERP techniques, the present study investigated neural correlates underlying the mirror reading of Chinese characters, and whether the cognitive processes underlying the recognition of mirrored Chinese characters is different from those of alphabetic words. Twelve native Chinese speakers participated in the experiment, during which they were instructed to make an animal/nonanimal distinction. The stimuli varied with the word category (animal vs nonanimal) and presentation format (normal vs mirror-reversed). The data analyses focused on three aspects: the reaction times (RT) for Chinese words of normal and mirror-reversed formats, peak latencies, and peak amplitudes of ERP components elicited by mirror-reversed and normal Chinese words. The results from implicit reading provide evidence for a mirror-reversed effect. The behavioural data showed that mirror-reversed words were more difficult to identify than normal words, with RTs delayed for mirror-reversed words over normal words. Moreover, a clear N2 component, with maximal activity occurring at 200-250ms interval (N2), was more negative for mirror-reversed words than for normal words at posterior regions. However, there were no latency differences between normal and mirror-reversed words. The occipital N2 might be closely related to abstract word form representation. Larger N2 amplitude in response to mirror-reversed Chinese words is interpreted as reflecting visuospatial transformation in order to compensate for impaired word form analysis. The result of no N2 latency delay indicated that word form analysis

  2. A Bayesian computational model for online character recognition and disability assessment during cursive eye writing

    Directory of Open Access Journals (Sweden)

    Julien eDiard

    2013-11-01

    Full Text Available This research involves a novel apparatus, in which the user is presented with an illusion inducing visual stimulus. The user perceives illusory movement that can be followed by the eye, so that smooth pursuit eye movements can be sustained in arbitrary directions. Thus, free-flow trajectories of any shape can be traced. In other words, coupled with an eye-tracking device, this apparatus enables "eye writing", which appears to be an original object of study. We adapt a previous model of reading and writing to this context. We describe a probabilistic model called the Bayesian Action-Perception for Eye On-Line model (BAP-EOL. It encodes probabilistic knowledge about isolated letter trajectories, their size, high-frequency components of the produced trajectory, and pupil diameter. We show how Bayesian inference, in this single model, can be used to solve several tasks, like letter recognition and novelty detection (i.e., recognizing when a presented character is not part of the learned database. We are interested in the potential use of the eye writing apparatus by motor impaired patients: the final task we solve by Bayesian inference is disability assessment (i.e., measuring and tracking the evolution of motor characteristics of produced trajectories. Preliminary experimental results are presented, which illustrate the method, showing the feasibility of character recognition in the context of eye writing. We then show experimentally how a model of the unknown character can be used to detect trajectories that are likely to be new symbols, and how disability assessment can be performed by opportunistically observing characteristics of fine motor control, as letter are being traced. Experimental analyses also help identify specificities of eye writing, as compared to handwriting, and the resulting technical challenges.

  3. Recognition of Non-Compound Handwritten Devnagari Characters using a Combination of MLP and Minimum Edit Distance

    CERN Document Server

    Arora, Sandhya; Nasipuri, Mita; Basu, D K; Kundu, M

    2010-01-01

    This paper deals with a new method for recognition of offline Handwritten non-compound Devnagari Characters in two stages. It uses two well known and established pattern recognition techniques: one using neural networks and the other one using minimum edit distance. Each of these techniques is applied on different sets of characters for recognition. In the first stage, two sets of features are computed and two classifiers are applied to get higher recognition accuracy. Two MLP's are used separately to recognize the characters. For one of the MLP's the characters are represented with their shadow features and for the other chain code histogram feature is used. The decision of both MLP's is combined using weighted majority scheme. Top three results produced by combined MLP's in the first stage are used to calculate the relative difference values. In the second stage, based on these relative differences character set is divided into two. First set consists of the characters with distinct shapes and second set co...

  4. Scanners, optical character readers, Cyrillic alphabet and Russian translations

    Science.gov (United States)

    Johnson, Gordon G.

    1995-01-01

    The writing of code for capture, in a uniform format, of bit maps of words and characters from scanner PICT files is presented. The coding of Dynamic Pattern Matched for the identification of the characters, words and sentences in preparation for translation is discussed.

  5. Effective Learning Strategies for the Recognition of Characters and Words by Learners of Chinese with Varying Proficiency in Different Learning Environments

    Directory of Open Access Journals (Sweden)

    Jing Wang

    2016-10-01

    Full Text Available The present study gauges effective strategies for recognizing characters and words by learners of Chinese as a foreign language. Besides answering background questions, 203 participants completed a questionnaire, a vocabulary recognition test, and a vocabulary checklist. The vocabulary test was found to be valid and reliable, and six categories of learning strategies were generated from the questionnaire. With the two background variables of language proficiency and language environment (studying abroad versus studying at home, the six strategy categories explained 48% of the variance in vocabulary recognition. Specifically, “frequent meaningful interaction with characters and words” positively predicted vocabulary recognition, whereas “focusing on character orthography” and “focusing on character pronunciation” negatively predicted it. The individual strategy of typing characters positively predicted vocabulary recognition, whereas using Pinyin to help remember pronunciation negatively predicted it. Pinyin can facilitate vocabulary recognition through typing characters yet may hinder it if excessively relying on Pinyin for pronunciation.

  6. Optical pattern recognition for printed music notation

    Science.gov (United States)

    Homenda, Wladyslaw

    1995-03-01

    The paper presents problems related to automated recognition of printed music notation. Music notation recognition is a challenging problem in both fields: pattern recognition and knowledge representation. Music notation symbols, though well characterized by their features, are arranged in elaborated way in real music notation, which makes recognition task very difficult and still open for new ideas. On the other hand, the aim of the system, i.e. application of acquired printed music into further processing requires special representation of music data. Due to complexity of music nature and music notation, music representation is one of the key issue in music notation recognition and music processing. The problems of pattern recognition and knowledge representation in context or music processing are discussed in this paper. MIDISCAN, the computer system for music notation recognition and music processing, is presented.

  7. Morphological Structure Processing during Word Recognition and Its Relationship to Character Reading among Third-Grade Chinese Children

    Science.gov (United States)

    Liu, Duo; McBride-Chang, Catherine

    2014-01-01

    In the present study, we explored the characteristics of morphological structure processing during word recognition among third grade Chinese children and its possible relationship with Chinese character reading. By using the modified priming lexical decision paradigm, a significant morphological structure priming effect was found in the subject…

  8. Preliminary Study of the Effect of Incremental Rehearsal with a Morphological Component for Teaching Chinese Character Recognition

    Science.gov (United States)

    Kwong, Elena; Burns, Matthew K.

    2016-01-01

    The current study examined the effectiveness of Incremental Rehearsal (IR) for teaching Chinese character recognition using a single-case experimental design. In addition, a morphological component was added to standard IR procedures (IRM) to take into account the role of morphological awareness in Chinese reading. Three kindergarten students in…

  9. High speed optical object recognition processor with massive holographic memory

    Science.gov (United States)

    Chao, T.; Zhou, H.; Reyes, G.

    2002-01-01

    Real-time object recognition using a compact grayscale optical correlator will be introduced. A holographic memory module for storing a large bank of optimum correlation filters, to accommodate the large data throughput rate needed for many real-world applications, has also been developed. System architecture of the optical processor and the holographic memory will be presented. Application examples of this object recognition technology will also be demonstrated.

  10. An optical processor for object recognition and tracking

    Science.gov (United States)

    Sloan, J.; Udomkesmalee, S.

    1987-01-01

    The design and development of a miniaturized optical processor that performs real time image correlation are described. The optical correlator utilizes the Vander Lugt matched spatial filter technique. The correlation output, a focused beam of light, is imaged onto a CMOS photodetector array. In addition to performing target recognition, the device also tracks the target. The hardware, composed of optical and electro-optical components, occupies only 590 cu cm of volume. A complete correlator system would also include an input imaging lens. This optical processing system is compact, rugged, requires only 3.5 watts of operating power, and weighs less than 3 kg. It represents a major achievement in miniaturizing optical processors. When considered as a special-purpose processing unit, it is an attractive alternative to conventional digital image recognition processing. It is conceivable that the combined technology of both optical and ditital processing could result in a very advanced robot vision system.

  11. Adaptive membership functions for handwritten character recognition by Voronoi-based image zoning.

    Science.gov (United States)

    Pirlo, Giuseppe; Impedovo, Donato

    2012-09-01

    In the field of handwritten character recognition, image zoning is a widespread technique for feature extraction since it is rightly considered to be able to cope with handwritten pattern variability. As a matter of fact, the problem of zoning design has attracted many researchers who have proposed several image-zoning topologies, according to static and dynamic strategies. Unfortunately, little attention has been paid so far to the role of feature-zone membership functions that define the way in which a feature influences different zones of the zoning method. The result is that the membership functions defined to date follow nonadaptive, global approaches that are unable to model local information on feature distributions. In this paper, a new class of zone-based membership functions with adaptive capabilities is introduced and its effectiveness is shown. The basic idea is to select, for each zone of the zoning method, the membership function best suited to exploit the characteristics of the feature distribution of that zone. In addition, a genetic algorithm is proposed to determine-in a unique process-the most favorable membership functions along with the optimal zoning topology, described by Voronoi tessellation. The experimental tests show the superiority of the new technique with respect to traditional zoning methods.

  12. Existence problem of optical correlation based pattern recognition

    Institute of Scientific and Technical Information of China (English)

    ZHANG; Yanxin(张延炘); LI; Sumei(李素梅)

    2003-01-01

    The existence problem of optical correlation based pattern recognition, namely its range of validity and its limitation, is discussed in this paper conjointly with the function approximation theory of neural networks. The conclusion is that only if the sets to be recognized are linearly separable (which is rare) or the subsets, in which a segmental sample of the targets is involved,are linearly separable, can the classical 4f optical correlation system carry out the task of recognition inerrably. The recognition principle of a joint transform correlator is the same as that of a 4f system, and so is its range of validities. Based on the demonstration of the existence problem of optical correlation based pattern recognition an evaluation on some important problems that were studied in this field over the past 40 years is presented explicitly.

  13. Chinese Character Recognition Based on ART Neural Network%基于ART神经网络的汉字识别

    Institute of Scientific and Technical Information of China (English)

    李龙; 戴凤智; 于春雨; 李玢瑶; 张峻霞

    2013-01-01

    针对汉字的多样性和相似性不同于西方字母,识别相对困难的问题,提出了基于 ART 神经网络的汉字识别方法。在识别前,利用 OpenCV(开源计算机视觉库)将汉字进行图像处理,为后续识别提供输入数据;然后经 ART 神经网络对输入数据进行训练识别。采用8组相似度较高的汉字作为样本进行实验,证明了方法的有效性。%Ouring to the differences between Chinese and western words and the difficulty in recognition,a Chinese charac-ter recognition model based on the ART neural network is proposed. Before recognition,the Chinese characters are processed by OpenCV(open source computer vision library),which provides input data for the following recognition procedure. Then, the input data are trained and recognized by ART neural network. In the experiment,eight groups of similar Chinese charac-ters were used as samples for the sake of making the results universal. The results show that the recognition of the shape-changed Chinese characters among the provided samples is reliable and accurate.

  14. Optodigital implementation of a neural network using a joint transform correlator based in a Hopfield inner product model for character recognition

    Science.gov (United States)

    Serrano-Heredia, A.; Hinojosa, C. M.; Ponce, R.; Arrizon, V.

    2003-11-01

    Systems for automatic pattern recognition can be performed by Artificial Neural Networks and Optical Correlators. Here, we present the design and implementation of a scheme which takes the advantages of both systems to develop an hybrid opto-digital processor, with applications in character recognition. The implementation of this system is based in the Hopfield inner products model using a Joint Transform Correlator. The procedure of recognition has the following steps: since a correlation peak is proportional to the inner product, the Hopfield method computes the inner product of the input and each memory using the Hybrid Opto-Digital Joint Transform Correlator. The second step performs a multiplication between the inner product and its respective memory, all this scaled images are added to get the future state of the input. The associative memory is replaced by two images with information of all images in the memory, this memories are added in the last step. The signal output is threshold and feedback as an input for the next iteration. The process stops when the output image does not change in the next iteration. The final image corresponds to the closest image in the memory of the signal input. This implementation is strong and has low cost, with potential applications for real time pattern recognition.

  15. Radial Wavelet Neural Network with a Novel Self-Creating Disk-Cell-Splitting Algorithm for License Plate Character Recognition

    Directory of Open Access Journals (Sweden)

    Rong Cheng

    2015-06-01

    Full Text Available In this paper, a novel self-creating disk-cell-splitting (SCDCS algorithm is proposed for training the radial wavelet neural network (RWNN model. Combining with the least square (LS method which determines the linear weight coefficients, SCDCS can create neurons adaptively on a disk according to the distribution of input data and learning goals. As a result, a disk map is made for input data as well as a RWNN model with proper architecture and parameters can be decided for the recognition task. The proposed SCDCS-LS based RWNN model is employed for the recognition of license plate characters. Compared to the classical radial-basis-function (RBF network with K-means clustering and LS, the proposed model can make a better recognition performance even with fewer neurons.

  16. Performance evaluation of MLP and RBF feed forward neural network for the recognition of off-line handwritten characters

    Science.gov (United States)

    Rishi, Rahul; Choudhary, Amit; Singh, Ravinder; Dhaka, Vijaypal Singh; Ahlawat, Savita; Rao, Mukta

    2010-02-01

    In this paper we propose a system for classification problem of handwritten text. The system is composed of preprocessing module, supervised learning module and recognition module on a very broad level. The preprocessing module digitizes the documents and extracts features (tangent values) for each character. The radial basis function network is used in the learning and recognition modules. The objective is to analyze and improve the performance of Multi Layer Perceptron (MLP) using RBF transfer functions over Logarithmic Sigmoid Function. The results of 35 experiments indicate that the Feed Forward MLP performs accurately and exhaustively with RBF. With the change in weight update mechanism and feature-drawn preprocessing module, the proposed system is competent with good recognition show.

  17. Automatic Recognition Method for Optical Measuring Instruments Based on Machine Vision

    Institute of Scientific and Technical Information of China (English)

    SONG Le; LIN Yuchi; HAO Liguo

    2008-01-01

    Based on a comprehensive study of various algorithms, the automatic recognition of traditional ocular optical measuring instruments is realized. Taking a universal tools microscope (UTM) lens view image as an example, a 2-layer automatic recognition model for data reading is established after adopting a series of pre-processing algorithms. This model is an optimal combination of the correlation-based template matching method and a concurrent back propagation (BP) neural network. Multiple complementary feature extraction is used in generating the eigenvectors of the concurrent network. In order to improve fault-tolerance capacity, rotation invariant features based on Zernike moments are extracted from digit characters and a 4-dimensional group of the outline features is also obtained. Moreover, the operating time and reading accuracy can be adjusted dynamically by setting the threshold value. The experimental result indicates that the newly developed algorithm has optimal recognition precision and working speed. The average reading ratio can achieve 97.23%. The recognition method can automatically obtain the results of optical measuring instruments rapidly and stably without modifying their original structure, which meets the application requirements.

  18. Using Singular Value Decomposition to Investigate Degraded Chinese Character Recognition: Evidence from Eye Movements during Reading

    Science.gov (United States)

    Wang, Hsueh-Cheng; Schotter, Elizabeth R.; Angele, Bernhard; Yang, Jinmian; Simovici, Dan; Pomplun, Marc; Rayner, Keith

    2013-01-01

    Previous research indicates that removing initial strokes from Chinese characters makes them harder to read than removing final or internal ones. In the present study, we examined the contribution of important components to character configuration via singular value decomposition. The results indicated that when the least important segments, which…

  19. The Effects of Graphic Similarity on Japanese Recognition of Simplified Chinese Characters

    Science.gov (United States)

    Teng, Xiaochun; Yamada, Jun

    2017-01-01

    The pedagogical and theoretical questions addressed in this study relate to the extent to which native Japanese readers with little or no knowledge of Chinese characters recognize Chinese characters that are viewed as abbreviations of the kanji they already know. Three graphic similarity functions (i.e., an orthographically acceptable similarity,…

  20. Sublexical Processing in Visual Recognition of Chinese Characters: Evidence from Repetition Blindness for Subcharacter Components

    Science.gov (United States)

    Yeh, Su-Ling; Li, Jing-Ling

    2004-01-01

    Repetition blindness (RB) refers to the failure to detect the second occurrence of a repeated item in rapid serial visual presentation (RSVP). In two experiments using RSVP, the ability to report two critical characters was found to be impaired when these two characters were identical (Experiment 1) or similar by sharing one repeated component…

  1. OFF-LINE HANDWRITING RECOGNITION USING VARIOUS HYBRID MODELING TECHNIQUES AND CHARACTER N-GRAMS

    NARCIS (Netherlands)

    Brakensiek, A.; Rottland, J.; Kosmala, A.; Rigoll, G.

    2004-01-01

    In this paper a system for on-line cursive handwriting recognition is described. The system is based on Hidden Markov Models (HMMs) using discrete and hybrid modeling techniques. Here, we focus on two aspects of the recognition system. First, we present different hybrid modeling techniques, whereas

  2. Comparison of computer-based and optical face recognition paradigms

    Science.gov (United States)

    Alorf, Abdulaziz A.

    The main objectives of this thesis are to validate an improved principal components analysis (IPCA) algorithm on images; designing and simulating a digital model for image compression, face recognition and image detection by using a principal components analysis (PCA) algorithm and the IPCA algorithm; designing and simulating an optical model for face recognition and object detection by using the joint transform correlator (JTC); establishing detection and recognition thresholds for each model; comparing between the performance of the PCA algorithm and the performance of the IPCA algorithm in compression, recognition and, detection; and comparing between the performance of the digital model and the performance of the optical model in recognition and detection. The MATLAB(c) software was used for simulating the models. PCA is a technique used for identifying patterns in data and representing the data in order to highlight any similarities or differences. The identification of patterns in data of high dimensions (more than three dimensions) is too difficult because the graphical representation of data is impossible. Therefore, PCA is a powerful method for analyzing data. IPCA is another statistical tool for identifying patterns in data. It uses information theory for improving PCA. The joint transform correlator (JTC) is an optical correlator used for synthesizing a frequency plane filter for coherent optical systems. The IPCA algorithm, in general, behaves better than the PCA algorithm in the most of the applications. It is better than the PCA algorithm in image compression because it obtains higher compression, more accurate reconstruction, and faster processing speed with acceptable errors; in addition, it is better than the PCA algorithm in real-time image detection due to the fact that it achieves the smallest error rate as well as remarkable speed. On the other hand, the PCA algorithm performs better than the IPCA algorithm in face recognition because it offers

  3. An examination of semantic radical combinability effects with lateralized cues in Chinese character recognition.

    Science.gov (United States)

    Hsiao, Janet Hui-Wen; Shillcock, Richard; Lavidor, Michal

    2007-04-01

    Auclair and Siéroff examined lateralized cuing effects in the identification of centrally presented letter strings and reported no cuing effects for short word stimuli. They argued for a redistribution of attention over the entire word for short familiar words. We explored cuing effects with Chinese phonetic compounds, which can be considered extreme examples of short words, in a character-level semantic judgment task. When the semantic radical position was placed on the left of the characters, strong radical combinability and semantic transparency effects were observed. There was also a significant interaction between cue position (left vs. right) and radical combinability: A left cue facilitated semantic judgment of characters with small radical combinability more than did a right cue. This behavior reflects the information profile of Chinese phonetic compounds. Semantic radicals with small combinability are more informative than those with large combinability in determining the meaning of the whole character; they therefore benefit more from a left than a right cue. A mechanism redistributing attention over the whole of the character was not in evidence at the level of semantic processing.

  4. Learning representation hierarchies by sharing visual features: a computational investigation of Persian character recognition with unsupervised deep learning.

    Science.gov (United States)

    Sadeghi, Zahra; Testolin, Alberto

    2017-08-01

    In humans, efficient recognition of written symbols is thought to rely on a hierarchical processing system, where simple features are progressively combined into more abstract, high-level representations. Here, we present a computational model of Persian character recognition based on deep belief networks, where increasingly more complex visual features emerge in a completely unsupervised manner by fitting a hierarchical generative model to the sensory data. Crucially, high-level internal representations emerging from unsupervised deep learning can be easily read out by a linear classifier, achieving state-of-the-art recognition accuracy. Furthermore, we tested the hypothesis that handwritten digits and letters share many common visual features: A generative model that captures the statistical structure of the letters distribution should therefore also support the recognition of written digits. To this aim, deep networks trained on Persian letters were used to build high-level representations of Persian digits, which were indeed read out with high accuracy. Our simulations show that complex visual features, such as those mediating the identification of Persian symbols, can emerge from unsupervised learning in multilayered neural networks and can support knowledge transfer across related domains.

  5. Feature Selection Method Based on Neighborhood Relationships: Applications in EEG Signal Identification and Chinese Character Recognition

    Directory of Open Access Journals (Sweden)

    Yu-Xiang Zhao

    2016-06-01

    Full Text Available In this study, a new feature selection algorithm, the neighborhood-relationship feature selection (NRFS algorithm, is proposed for identifying rat electroencephalogram signals and recognizing Chinese characters. In these two applications, dependent relationships exist among the feature vectors and their neighboring feature vectors. Therefore, the proposed NRFS algorithm was designed for solving this problem. By applying the NRFS algorithm, unselected feature vectors have a high priority of being added into the feature subset if the neighboring feature vectors have been selected. In addition, selected feature vectors have a high priority of being eliminated if the neighboring feature vectors are not selected. In the experiments conducted in this study, the NRFS algorithm was compared with two feature algorithms. The experimental results indicated that the NRFS algorithm can extract the crucial frequency bands for identifying rat vigilance states and identifying crucial character regions for recognizing Chinese characters.

  6. Feature Selection Method Based on Neighborhood Relationships: Applications in EEG Signal Identification and Chinese Character Recognition

    Science.gov (United States)

    Zhao, Yu-Xiang; Chou, Chien-Hsing

    2016-01-01

    In this study, a new feature selection algorithm, the neighborhood-relationship feature selection (NRFS) algorithm, is proposed for identifying rat electroencephalogram signals and recognizing Chinese characters. In these two applications, dependent relationships exist among the feature vectors and their neighboring feature vectors. Therefore, the proposed NRFS algorithm was designed for solving this problem. By applying the NRFS algorithm, unselected feature vectors have a high priority of being added into the feature subset if the neighboring feature vectors have been selected. In addition, selected feature vectors have a high priority of being eliminated if the neighboring feature vectors are not selected. In the experiments conducted in this study, the NRFS algorithm was compared with two feature algorithms. The experimental results indicated that the NRFS algorithm can extract the crucial frequency bands for identifying rat vigilance states and identifying crucial character regions for recognizing Chinese characters. PMID:27314346

  7. Feature Selection Method Based on Neighborhood Relationships: Applications in EEG Signal Identification and Chinese Character Recognition.

    Science.gov (United States)

    Zhao, Yu-Xiang; Chou, Chien-Hsing

    2016-06-14

    In this study, a new feature selection algorithm, the neighborhood-relationship feature selection (NRFS) algorithm, is proposed for identifying rat electroencephalogram signals and recognizing Chinese characters. In these two applications, dependent relationships exist among the feature vectors and their neighboring feature vectors. Therefore, the proposed NRFS algorithm was designed for solving this problem. By applying the NRFS algorithm, unselected feature vectors have a high priority of being added into the feature subset if the neighboring feature vectors have been selected. In addition, selected feature vectors have a high priority of being eliminated if the neighboring feature vectors are not selected. In the experiments conducted in this study, the NRFS algorithm was compared with two feature algorithms. The experimental results indicated that the NRFS algorithm can extract the crucial frequency bands for identifying rat vigilance states and identifying crucial character regions for recognizing Chinese characters.

  8. The use of invariant moments in hand-written character recognition

    Directory of Open Access Journals (Sweden)

    Dan L. Lacrama

    2006-01-01

    Full Text Available The goal of this paper is to present the implementation of a Radial Basis Function neural network with built-in knowledge to recognize hand-written characters. The neural network includes in its architecture gates controlled by an attraction/repulsion system of coefficients. These coefficients are derived from a preprocessing stage which groups the characters according to their ascendant, central, or descendent components.The neural network is trained using data from invariant moment functions. Results are compared with those obtained using a K nearest neighbor method on the same moment data.

  9. The Effect of Computer-Based Multimedia Instruction with Chinese Character Recognition

    Science.gov (United States)

    Chuang, Hui-Ya; Ku, Heng-Yu

    2011-01-01

    The purpose of this study was to examine second language learners' learning achievement and attitudes toward two different types of dual coding designs (text group: image plus on-screen text versus narration group: image plus narration) in Chinese character acquisition. A total of 66 college students who did not have prior knowledge of the Chinese…

  10. Linear Invariant Multiclass Component Spaces For Optical Pattern Recognition

    Science.gov (United States)

    Hester, Charles F.

    1983-04-01

    Optical processing systems which perform linear transformations on image data at high rates are ideal for image pattern recognition systems. As a result of this processing capability, the linear opera-tion of matched spatial filtering has been explored extensively for pattern recognition. For many practical pattern recognition problems, however, multiclass filtering must be used to overcome the variations of input objects due to image scale changes, image rotations, object aspect differences and sensor differences. Hester and Casasent have shown that a linear mapping can be constructed which images all the class elements of a multiclass set into one out-put element or value. This special multi-class filter concept is extended in this paper to show that a subspace of the multi-class set exists that is invariant with respect to the multiclass mapping under linear operations. The concept of this in-variant space and its generation is detailed and a single example given. A typical optical processing architecture using these invariant elements as filters in an associative pattern recognition system is also presented.

  11. Multiclass optical correlation filters for alphanumeric field recognition

    Science.gov (United States)

    Casasent, David P.; Gopalaswamy, Srinivasan; Iyer, Anand K.

    1993-01-01

    We consider the use of new distortion-invariant optical correlation filters for machine-printed OCR. Our work is unique in its treatment of a large set of different fonts, printer types, plus rotations and scale (point size) variations, and various practical issues such as printing artifacts and background noise. We detail their use in the locations and recognition of alphanumeric fluids (digits) in destination address blocks (DABs).

  12. License plate character recognition based on the MQDF%基于MQDF的车牌字符识别

    Institute of Scientific and Technical Information of China (English)

    周明辉; 刘辉; 曹刚

    2013-01-01

    This paper proposed a new license plate character recognition algorithm based on MQDF,which includes K-L transformation based on the QDF,and replaces the small characteristic value with constant to improve the calculation speed and classification accuracy.The method based on the statistical model and central limit theorem,which is easy to design,implementation,and widely used in handwriting recognition,has the very good robustness and higher identification accuracy.With the experiment of the license plate image of 2142 of the day,evening blue yellow card,the results show that,average recognition rate reaches above 98% for digit,letter,Chinese characters,which has a good applied foreground.%文中提出了一种新的基于MQDF的车牌字符识别算法,该算法在QDF的基础上进行K-L变换,并且用常量代替小的特征值改善计算速度和分类的正确率.该方法基于统计模型和中心极限定理,便于设计和实现,广泛应用于手写体识别,具有很好的鲁棒性和较高的识别准确率.用2142幅白天、晚上的蓝牌、黄牌车牌图像做实验,实验结果表明,对于数字、字母、汉字字符,平均识别率达到98%以上,具有较好的应用前景.

  13. 基于模板匹配法的字符识别算法研究%The Research of Character Recognition Algorithm in Template Matching Method

    Institute of Scientific and Technical Information of China (English)

    李新良

    2012-01-01

    This paper first discussed the concept of character recognition, process and template matching principle;second, from the algorithm process and the key code focused on the three template—based character recognition algorithm; and again comparative analysised seven different state rate and the character of false consciousness; last it offered an optional basis for the industrial character recognition in the identification of from the performance of the recognition rate and time to compare the pros and cons of the three character recognition algorithm.%对字符识别概念、过程和模板匹配法的原理进行探讨;从算法流程、关键代码等方面重点研究三种基于模板的字符识别算法;然后通过字符在七种不同状态下的识别率与误识字符进行对比分析;从识别率和时间性能上比较三种字符识别算法的优劣,为工业字符识别提供可选依据.

  14. Noise tolerance in optical waveguide circuits for recognition of optical 16 quadrature amplitude modulation codes

    Science.gov (United States)

    Inoshita, Kensuke; Hama, Yoshimitsu; Kishikawa, Hiroki; Goto, Nobuo

    2016-12-01

    In photonic label routers, various optical signal processing functions are required; these include optical label extraction, recognition of the label, optical switching and buffering controlled by signals based on the label information and network routing tables, and label rewriting. Among these functions, we focus on photonic label recognition. We have proposed two kinds of optical waveguide circuits to recognize 16 quadrature amplitude modulation codes, i.e., recognition from the minimum output port and from the maximum output port. The recognition function was theoretically analyzed and numerically simulated by finite-difference beam-propagation method. We discuss noise tolerance in the circuit and show numerically simulated results to evaluate bit-error-rate (BER) characteristics against optical signal-to-noise ratio (OSNR). The OSNR required to obtain a BER less than 1.0×10-3 for the symbol rate of 2.5 GBaud was 14.5 and 27.0 dB for recognition from the minimum and maximum output, respectively.

  15. Do dyslexic individuals present a reduced visual attention span? Evidence from visual recognition tasks of non-verbal multi-character arrays.

    Science.gov (United States)

    Yeari, Menahem; Isser, Michal; Schiff, Rachel

    2016-06-21

    A controversy has recently developed regarding the hypothesis that developmental dyslexia may be caused, in some cases, by a reduced visual attention span (VAS). To examine this hypothesis, independent of phonological abilities, researchers tested the ability of dyslexic participants to recognize arrays of unfamiliar visual characters. Employing this test, findings were rather equivocal: dyslexic participants exhibited poor performance in some studies but normal performance in others. The present study explored four methodological differences revealed between the two sets of studies that might underlie their conflicting results. Specifically, in two experiments we examined whether a VAS deficit is (a) specific to recognition of multi-character arrays as wholes rather than of individual characters within arrays, (b) specific to characters' position within arrays rather than to characters' identity, or revealed only under a higher attention load due to (c) low-discriminable characters, and/or (d) characters' short exposure. Furthermore, in this study we examined whether pure dyslexic participants who do not have attention disorder exhibit a reduced VAS. Although comorbidity of dyslexia and attention disorder is common and the ability to sustain attention for a long time plays a major rule in the visual recognition task, the presence of attention disorder was neither evaluated nor ruled out in previous studies. Findings did not reveal any differences between the performance of dyslexic and control participants on eight versions of the visual recognition task. These findings suggest that pure dyslexic individuals do not present a reduced visual attention span.

  16. Enhancement and character recognition of the erased colophon of a 15th-century Hebrew prayer book

    Science.gov (United States)

    Walvoord, Derek J.; Easton, Roger L., Jr.; Knox, Keith T.; Heimbueger, Matthew

    2005-01-01

    A handwritten codex often included an inscription that listed facts about its publication, such as the names of the scribe and patron, date of publication, the city where the book was copied, etc. These facts obviously provide essential information to a historian studying the provenance of the codex. Unfortunately, this page was sometimes erased after the sale of the book to a new owner, often by scraping off the original ink. The importance of recovering this information would be difficult to overstate. This paper reports on the methods of imaging, image enhancement, and character recognition that were applied to this page in a Hebrew prayer book copied in Florence in the 15th century.

  17. A Markov chain based line segmentation framework for handwritten character recognition

    Science.gov (United States)

    Wu, Yue; Zha, Shengxin; Cao, Huaigu; Liu, Daben; Natarajan, Premkumar

    2013-12-01

    In this paper, we present a novel text line segmentation framework following the divide-and-conquer paradigm: we iteratively identify and re-process regions of ambiguous line segmentation from an input document image until there is no ambiguity. To detect ambiguous line segmentation, we introduce the use of two complimentary line descriptors, referred as to the underline and highlight line descriptors, and identify ambiguities when their patterns mismatch. As a result, we can easily identify already good line segmentations, and largely simplify the original line segmentation problem by only reprocessing ambiguous regions. We evaluate the performance of the proposed line segmentation framework using the ICDAR 2009 handwritten document dataset, and it is close to top-performing systems submitted to the competition. Moreover, the proposed method is also robust against skewness, noise, variable line heights and touching characters. The proposed idea can also be applied to other text analysis tasks such as word segmentation and page layout analysis.

  18. Visual Guide Technology Based on Character Recognition and ROI%字符识别耦合的ROI视觉引导应用

    Institute of Scientific and Technical Information of China (English)

    王帮元

    2015-01-01

    字符是标识产品的重要信息,由于产品表面成像画质多样性,当字符目标不清晰或者背景干扰大,往往会影响识别算法的精准度. 鉴于此,提出了一个基于Emgucv与Tesseract的字符识别机制,用来识别平板电脑表面薄膜字符. 首先利用网络摄像头,对平板电脑表面薄膜字符区域取像;再对获取的灰度图进行阈值分割得到包含目标的二值图;然后利用形态学处理去除杂质干扰、提取目标特征,得出感兴趣区域(ROI);最后基于Tesseract开源库,实现对ROI区域的字符识别. 整个系统图像处理部分由C#和Emgucv实现,根据字符识别结果,用运动控制卡传递命令给机构,对薄膜进行分流,完成视觉引导. 通过实验测试本文字符识别系统性能,结果表明本机制与当前字符识别技术相比具有更好的识别效果.%Character is important information identifying a product. Owing to the product surface imaging quality diversity, with the character not clear or background interference, the accuracy of recognition algorithm would be greatly influenced. Therefore, this paper proposes a character recognition mechanism based on Emgucv and Tesseract to identify the tablet PC's surface film character. First, to capture the tablet PC's surface film character area via a webcam. Then, to harvest a binary image containing the character object via making threshold segmentation in the grey-scale map obtained. Third, to get ROI region via wiping off impurity. Finally, based on the open source Tesseract library, to realize the character recognition in ROI region. The image processing in the whole system is achieved by C# and Emgucv, according to the character recognition results, the films were shunt based on the motion control card to send orders to complete visual guide. It comes to a conclusion that this mechanism has better recognition effect compared with the current character recognition technology.

  19. Summary of the transfer of optical processing to systems: optical pattern recognition program

    Science.gov (United States)

    Lindell, Scott D.

    1995-06-01

    Martin Marietta has successfully completed a TOPS optical pattern recognition program. The program culminated in August 1994 with an automatic target recognition flight demonstration inwhich an M60A2 tank was acquired, identified, and tracked with a visible seeker from a UH-1 helicopter flying a fiber optic guided missile (FOG-M) mission profile. The flight demonstration was conducted by the US Army Missile Command (MICOM) and supported by Martin Marietta. The pattern recognition system performance for acquiring and identifying the M60A2 tank, which was positioned among an array with five other vehicle types, was 90% probability of correct identification and a 4% false identification for over 40,000 frames of imagery processed. Imagery was processed at a 15 Hz input rate with a 1 ft3, 76 W, 4 GFLOP processor performing up to 800 correlations per second.

  20. Evaluating Barten image metric for predicting character recognition in people with low vision.

    Science.gov (United States)

    Schoessow, Kimberly A; Mauney, Lisa M; Uslan, Mark; Schuchard, Ronald A

    2013-01-01

    Electronic devices with small visual displays (SVDs) are often inaccessible to the millions of Americans with vision loss. The Barten square root integral (SQRI) is an image quality metric that has been shown to predict whether people with normal vision can see images on a cathode ray tube monitor. The present proof-of-concept study begins to explore whether the same metric could predict the ability of users with low vision to see images on SVDs. In a sample population of 33 adults with low vision, the Barten SQRI was the best predictor of the ability to recognize low-contrast single digits on a screen (r(2) = 0.80, p < 0.01), followed by the Pelli-Robson Contrast Sensitivity Chart (r(2) = 0.69, p < 0.01). Visual acuity was not significantly predictive of the ability to read low-contrast characters on a display. Further work will explore whether the Barten SQRI remains predictive of the ability of people with low vision to use actual devices that have SVDs.

  1. Fabrication and characteristics of character1 shaped reduced diameter polarization-maintaining optical fiber

    Institute of Scientific and Technical Information of China (English)

    Jianxiang Wen; Letian Liang; Tianpeng Xiao; Xiaojun Xu; Hua Yu; Wu Su

    2006-01-01

    @@ A novel structure reducing diameter polarization maintaining optical fiber with high birefringence and strength is introduced.The fiber is fabricated through using modified chemical vapor deposition (MCVD) method,which is able to produce the optimum predicted character-1 shaped fiber structure.As a result,a low-loss fiber with beat length close to 2.0 mm at 1310 nm wavelength and extinction ratio approximately-25 dB has been produced.The process is both simple and reproducible.

  2. Native-Language Phonological Interference in Early Hakka-Mandarin Bilinguals' Visual Recognition of Chinese Two-Character Compounds: Evidence from the Semantic-Relatedness Decision Task

    Science.gov (United States)

    Wu, Shiyu; Ma, Zheng

    2017-01-01

    Previous research has indicated that, in viewing a visual word, the activated phonological representation in turn activates its homophone, causing semantic interference. Using this mechanism of phonological mediation, this study investigated native-language phonological interference in visual recognition of Chinese two-character compounds by early…

  3. Native-Language Phonological Interference in Early Hakka-Mandarin Bilinguals' Visual Recognition of Chinese Two-Character Compounds: Evidence from the Semantic-Relatedness Decision Task

    Science.gov (United States)

    Wu, Shiyu; Ma, Zheng

    2017-01-01

    Previous research has indicated that, in viewing a visual word, the activated phonological representation in turn activates its homophone, causing semantic interference. Using this mechanism of phonological mediation, this study investigated native-language phonological interference in visual recognition of Chinese two-character compounds by early…

  4. 基于结构化识别码的朝鲜文识别策略%A strategy of Korean character recognition based on structured identification code

    Institute of Scientific and Technical Information of China (English)

    崔荣一

    2000-01-01

    从文字识别的角度讨论了朝鲜文字母和文字的组成规则,采用字母结构化识别码分析了字母的基本要素与组成规律,并通过文字生成图和文字结构图分析了文字的时空特征.同时还讨论了文字复杂性的来源以及off-line手写体朝鲜文字识别的一种策略.%This paper discusses the combination rules of Korean grapheme and character from the point of view of character recognition. The essential components and combination rules of Korean grapheme are analyzed by adopting the structured identification code (ID-code), and the time-spece characteristics are analyzed with character generation diagram(CGD) and character structure diagram (CSD). The source of character complexity and a strategy of off-line handwritten Korean character recognition are also discussed.

  5. Enhanced e-beam pattern writing for nano-optics based on character projection

    Science.gov (United States)

    Kley, E.-Bernhard; Schmidt, Holger; Zeitner, Uwe; Banasch, Michael; Schnabel, Bernd

    2012-02-01

    The pattern generation for nano-optics raises high demands on resolution, writing speed and flexibility: nearly arbitrary complex structures with feature sizes below 100 nm should be realized on large areas up to 9 inches in square within reasonable time. With e-beam lithography the requirements on resolution and flexibility can be fulfilled but the writing time becomes the bottle neck. Acceleration by Variable Shaped Beam (VSB) writing principle (geometrical primitives with flexible size can be exposed with a single shot) is sometimes not sufficient. Character Projection (CP) is able to speed up the writing drastically because complex pattern of a limited area can be exposed by one shot [1]. We tested CP in the Vistec SB350 OS for optical applications and found a shot count reduction up to 1/1000, especially for geometries which are hard to approximate by geometrical primitives. Additionally, the resolution and the pattern quality were influenced in a positive way. Another benefit is the possibility to spend a part of the gain in writing speed to the use of a high resolution but low sensitive resist like HSQ. The tradeoff between speed and flexibility should be compensable by a large number of characters available.

  6. Lack of character displacement in the male recognition molecule, bindin, in Altantic sea urchins of the genus Echinometra.

    Science.gov (United States)

    Geyer, Laura B; Lessios, H A

    2009-09-01

    Bindin, a protein involved in sea urchin sperm-egg recognition and adhesion, is under positive selection in genera with sympatric species but evolves neutrally in genera in which all species are allopatric. This pattern has led to suggestions that reinforcement may be the source of the observed selection. Reproductive character displacement, or increased divergence of reproductive characters in areas where closely related species overlap, is often a consequence of reinforcement and has been shown to be present in one Indo-Pacific species of the genus Echinometra. In the Atlantic species of the same genus, positive selection has been shown to act on bindin of Echinometra lucunter. To examine whether the source of this selection is reinforcement, we determined variation on the first exon of bindin in E. lucunter in the Caribbean, where it is sympatric with Echinometra viridis, and in the rest of the Atlantic, where E. viridis is absent. There was no differentiation between bindin sequences from the two geographic regions; similar levels of positive selection were found to be acting in both areas. The similarities were not due to gene flow; mitochondrial DNA from the two regions indicates that E. lucunter populations most likely originated in the Atlantic and have not exchanged genes with Caribbean populations for approximately 200,000 years. The lack of evidence of stronger selection on bindin of E. lucunter in areas of sympatry with its sister species suggests that the source of selection is not reinforcement. Processes acting within species, such as sexual selection, sperm competition, or sexual conflict, are more likely to be involved in the evolution of this molecule.

  7. Visual Field Differences in Visual Word Recognition Can Emerge Purely from Perceptual Learning: Evidence from Modeling Chinese Character Pronunciation

    Science.gov (United States)

    Hsiao, Janet Hui-wen

    2011-01-01

    In Chinese orthography, a dominant character structure exists in which a semantic radical appears on the left and a phonetic radical on the right (SP characters); a minority opposite arrangement also exists (PS characters). As the number of phonetic radical types is much greater than semantic radical types, in SP characters the information is…

  8. Visual Field Differences in Visual Word Recognition Can Emerge Purely from Perceptual Learning: Evidence from Modeling Chinese Character Pronunciation

    Science.gov (United States)

    Hsiao, Janet Hui-wen

    2011-01-01

    In Chinese orthography, a dominant character structure exists in which a semantic radical appears on the left and a phonetic radical on the right (SP characters); a minority opposite arrangement also exists (PS characters). As the number of phonetic radical types is much greater than semantic radical types, in SP characters the information is…

  9. ONTOGENY, HOMOLOGY, AND TERMINOLOGY-WALL MORPHOGENESIS AS AN AID TO CHARACTER RECOGNITION AND CHARACTER STATE DEFINITION FOR PENNATE DIATOM SYSTEMATICS(1).

    Science.gov (United States)

    Cox, Eileen J

    2012-02-01

    This article reviews current knowledge of wall morphogenesis in pennate diatoms in relation to the way characters are defined and described for taxonomic and systematic analyses. It argues that an understanding of ontogeny is essential for the accurate identification of character homologies, which in turn must underpin all phylogenetic and systematic analyses. Terminology should reflect character homology, but most diatom terminology fails to do this, with concomitant confusion and potential taxonomic mistakes. Identifying where information is lacking or misinterpreted are first steps toward improving our understanding of diatom structure and relationships. After reviewing the current knowledge on pennate diatom structure and its development, this article briefly discusses the significance of morphological variation, character polarity, and the vital importance of applying diatom terminology correctly. © 2011 Phycological Society of America.

  10. Optical Music Recognition for Scores Written in White Mensural Notation

    Directory of Open Access Journals (Sweden)

    Antonio Oliver

    2009-01-01

    Full Text Available An Optical Music Recognition (OMR system especially adapted for handwritten musical scores of the XVII-th and the early XVIII-th centuries written in white mensural notation is presented. The system performs a complete sequence of analysis stages: the input is the RGB image of the score to be analyzed and, after a preprocessing that returns a black and white image with corrected rotation, the staves are processed to return a score without staff lines; then, a music symbol processing stage isolates the music symbols contained in the score and, finally, the classification process starts to obtain the transcription in a suitable electronic format so that it can be stored or played. This work will help to preserve our cultural heritage keeping the musical information of the scores in a digital format that also gives the possibility to perform and distribute the original music contained in those scores.

  11. Optical Music Recognition for Scores Written in White Mensural Notation

    Directory of Open Access Journals (Sweden)

    Tardón LorenzoJ

    2009-01-01

    Full Text Available An Optical Music Recognition (OMR system especially adapted for handwritten musical scores of the XVII-th and the early XVIII-th centuries written in white mensural notation is presented. The system performs a complete sequence of analysis stages: the input is the RGB image of the score to be analyzed and, after a preprocessing that returns a black and white image with corrected rotation, the staves are processed to return a score without staff lines; then, a music symbol processing stage isolates the music symbols contained in the score and, finally, the classification process starts to obtain the transcription in a suitable electronic format so that it can be stored or played. This work will help to preserve our cultural heritage keeping the musical information of the scores in a digital format that also gives the possibility to perform and distribute the original music contained in those scores.

  12. A Solution to Reconstruct Cross-Cut Shredded Text Documents Based on Character Recognition and Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    Hedong Xu

    2014-01-01

    Full Text Available The reconstruction of destroyed paper documents is of more interest during the last years. This topic is relevant to the fields of forensics, investigative sciences, and archeology. Previous research and analysis on the reconstruction of cross-cut shredded text document (RCCSTD are mainly based on the likelihood and the traditional heuristic algorithm. In this paper, a feature-matching algorithm based on the character recognition via establishing the database of the letters is presented, reconstructing the shredded document by row clustering, intrarow splicing, and interrow splicing. Row clustering is executed through the clustering algorithm according to the clustering vectors of the fragments. Intrarow splicing regarded as the travelling salesman problem is solved by the improved genetic algorithm. Finally, the document is reconstructed by the interrow splicing according to the line spacing and the proximity of the fragments. Computational experiments suggest that the presented algorithm is of high precision and efficiency, and that the algorithm may be useful for the different size of cross-cut shredded text document.

  13. Character recognition as an alternate measure of television exposure among children: findings from the Alam Simsim program in Egypt.

    Science.gov (United States)

    Rimal, Rajiv N; Figueroa, Maria Elena; Storey, J Douglas

    2013-01-01

    Evaluation of effects of mass media-based health interventions requires accurate assessments of exposure, which can be difficult to obtain when young children are the primary audience. Alam Simsim, the Egyptian version of Sesame Street, aired nationally in Egypt to teach preschoolers about numeracy, literacy, and gender-equitable attitudes. The purpose of this article was to assess the effect of the program through a first-of-its-kind household-level survey that interviewed caretakers (n = 426) and preschoolers (n = 486). The authors introduced and tested the efficacy of a parsimonious measure of exposure: children's recognition of the primary characters of the program. Overall, the authors' models explained as much as 53% of the variance in children's learning; exposure to the program was significantly associated with learning. Furthermore, the parsimonious measure of exposure was as effective as a more elaborate child-reported measure. Relative to these two measures of exposure, caretakers' report of children's viewing was not as good a predictor of learning.

  14. [Monitoring the sewage degradation by analyzing optic fiber SPR spectrum character].

    Science.gov (United States)

    Zhang, Xiao-Li; Liang, Da-Kai; Zeng, Jie; Zhao, Zhi-Yuan; Zeng, Jian-Min

    2010-02-01

    The working principle of the optic fiber SPR sensor was discussed in the present paper at first. The feasibility of using it to monitor the degradation process of the environmental sewage represented by the methyl orange was studied. Finally, the optic fiber SPR sensor was adopted to monitor the change in degradation concentration represented by the original methyl orange solution on the base of 50 mL initial concentration 30 mg x L(-1), and the optic fiber SPR spectrum character of degradation process was analyzed in detail. Meanwhile the UV spectrophotometer was used to measure the change in concentration in the course of the degradation. The measurement data were analyzed and compared at large. The research work indicates that both the methods have consistent results, as the degradation time increases, the absorbance and concentration of the environmental sewage represented by the methyl orange solution decrease by and by, and the resonant wavelength of the optic fiber SPR sensor blue shifts step by step, as compared to the original standardization methyl orange solution resonant spectrum. It was shown that the methyl orange solution was degraded, and the rate of degradation was up to about 73 percent within two hours. The comparative results illustrate that it is feasible to use the optic fiber SPR sensor to monitor the environmental sewage degradation. The research result not only provides a new monitoring method for the degradation process of the environmental sewage, but also promotes the technique of the SPR sensor combined to the environment monitor by a long way.

  15. TreeRipper web application: towards a fully automated optical tree recognition software

    Directory of Open Access Journals (Sweden)

    Hughes Joseph

    2011-05-01

    Full Text Available Abstract Background Relationships between species, genes and genomes have been printed as trees for over a century. Whilst this may have been the best format for exchanging and sharing phylogenetic hypotheses during the 20th century, the worldwide web now provides faster and automated ways of transferring and sharing phylogenetic knowledge. However, novel software is needed to defrost these published phylogenies for the 21st century. Results TreeRipper is a simple website for the fully-automated recognition of multifurcating phylogenetic trees (http://linnaeus.zoology.gla.ac.uk/~jhughes/treeripper/. The program accepts a range of input image formats (PNG, JPG/JPEG or GIF. The underlying command line c++ program follows a number of cleaning steps to detect lines, remove node labels, patch-up broken lines and corners and detect line edges. The edge contour is then determined to detect the branch length, tip label positions and the topology of the tree. Optical Character Recognition (OCR is used to convert the tip labels into text with the freely available tesseract-ocr software. 32% of images meeting the prerequisites for TreeRipper were successfully recognised, the largest tree had 115 leaves. Conclusions Despite the diversity of ways phylogenies have been illustrated making the design of a fully automated tree recognition software difficult, TreeRipper is a step towards automating the digitization of past phylogenies. We also provide a dataset of 100 tree images and associated tree files for training and/or benchmarking future software. TreeRipper is an open source project licensed under the GNU General Public Licence v3.

  16. Fuzzy - Based Method of Detecting the Enviroment Character for UAV Optical Stabilization

    Directory of Open Access Journals (Sweden)

    David Novak

    2015-01-01

    Full Text Available An optical stabilization of UAV (UAS is a very important part of a structure in their control systems. Not only as a backup stabilization system in a case of IMU failure, but also as a main system, used for stabilization or navigation. In this paper the concept of a system for environment character detection is presented. The system can classify a surrounding environment depending on chosen characteristics. Such system can be used for a better horizon detection due to switching to a correct horizon detection algorithm, which can be used for determining the position of UAV. The system is based on Takagi - Sugeno fuzzy inference system and fuzzy artificial neural networks. An earlier work on this subject was presented last year, but concept of the system was redesigned with a usage of fuzzy artificial neural network for a more precisive outputs and automatic determination of characteristics of fuzzy sets on input.

  17. Functional Anatomy of Recognition of Chinese Multi-Character Words: Convergent Evidence from Effects of Transposable Nonwords, Lexicality, and Word Frequency.

    Directory of Open Access Journals (Sweden)

    Nan Lin

    Full Text Available This fMRI study aimed to identify the neural mechanisms underlying the recognition of Chinese multi-character words by partialling out the confounding effect of reaction time (RT. For this purpose, a special type of nonword-transposable nonword-was created by reversing the character orders of real words. These nonwords were included in a lexical decision task along with regular (non-transposable nonwords and real words. Through conjunction analysis on the contrasts of transposable nonwords versus regular nonwords and words versus regular nonwords, the confounding effect of RT was eliminated, and the regions involved in word recognition were reliably identified. The word-frequency effect was also examined in emerged regions to further assess their functional roles in word processing. Results showed significant conjunctional effect and positive word-frequency effect in the bilateral inferior parietal lobules and posterior cingulate cortex, whereas only conjunctional effect was found in the anterior cingulate cortex. The roles of these brain regions in recognition of Chinese multi-character words were discussed.

  18. Functional Anatomy of Recognition of Chinese Multi-Character Words: Convergent Evidence from Effects of Transposable Nonwords, Lexicality, and Word Frequency.

    Science.gov (United States)

    Lin, Nan; Yu, Xi; Zhao, Ying; Zhang, Mingxia

    2016-01-01

    This fMRI study aimed to identify the neural mechanisms underlying the recognition of Chinese multi-character words by partialling out the confounding effect of reaction time (RT). For this purpose, a special type of nonword-transposable nonword-was created by reversing the character orders of real words. These nonwords were included in a lexical decision task along with regular (non-transposable) nonwords and real words. Through conjunction analysis on the contrasts of transposable nonwords versus regular nonwords and words versus regular nonwords, the confounding effect of RT was eliminated, and the regions involved in word recognition were reliably identified. The word-frequency effect was also examined in emerged regions to further assess their functional roles in word processing. Results showed significant conjunctional effect and positive word-frequency effect in the bilateral inferior parietal lobules and posterior cingulate cortex, whereas only conjunctional effect was found in the anterior cingulate cortex. The roles of these brain regions in recognition of Chinese multi-character words were discussed.

  19. Optical music recognition on the International Music Score Library Project

    Science.gov (United States)

    Raphael, Christopher; Jin, Rong

    2013-12-01

    A system is presented for optical recognition of music scores. The system processes a document page in three main phases. First it performs a hierarchical decomposition of the page, identifying systems, staves and measures. The second phase, which forms the heart of the system, interprets each measure found in the previous phase as a collection of non-overlapping symbols including both primitive symbols (clefs, rests, etc.) with fixed templates, and composite symbols (chords, beamed groups, etc.) constructed through grammatical composition of primitives (note heads, ledger lines, beams, etc.). This phase proceeds by first building separate top-down recognizers for the symbols of interest. Then, it resolves the inevitable overlap between the recognized symbols by exploring the possible assignment of overlapping regions, seeking globally optimal and grammatically consistent explanations. The third phase interprets the recognized symbols in terms of pitch and rhythm, focusing on the main challenge of rhythm. We present results that compare our system to the leading commercial OMR system using MIDI ground truth for piano music.

  20. Differential Hemispheric Processing in the Recognition of Chinese Characters with Different Structures in Foveal and Parafoveal Vision

    Directory of Open Access Journals (Sweden)

    Janet H. Hsiao

    2011-05-01

    Full Text Available Whether foveal representation in reading is initially split and contralaterally projected to different hemispheres or bilaterally projected remains a controversial issue. Here we examine visual field asymmetry effects in naming Chinese characters with different structures, with characters presented either to the left visual field or the right visual field (RVF, and either within or outside foveal vision (eccentricity. We show that overall the RVF advantage in naming characters was significant in both eccentricity conditions (fovea vs. parafovea, with a stronger effect in parafoveal vision. This suggests that foveal splitting may not be an all-or-none phenomenon but has a graded effect. When examining characters with different structures separately, this interaction between visual field and eccentricity was significant only in the dominant, right-heavy character structure type, but not in the minority left-heavy or symmetric structure types, suggesting a modulation of character structure or type frequency on the eccentricity effect. In addition, existence of a phonetic radical modulated the visual field asymmetry effect differentially in different character structure types; however this effect did not interact with eccentricity. This result thus suggests that character structure and existence of a phonetic radical have differential modulation on character processing in the foveal and parafoveal vision.

  1. Optical pattern recognition; Proceedings of the Meeting, Los Angeles, CA, Jan. 17, 18, 1989

    Science.gov (United States)

    Liu, Hua-Kuang (Editor)

    1989-01-01

    Papers on optical pattern recognition are presented, covering topics such as the estimation of satellite pose and motion parameters using a neural net tracker, associative memory, optical implmentation of programmable neural networks, optoelectronic neural networks, dynamic autoassociative neural memory, heteroassociative memory, bilinear pattern recognition processors, optical processing of optical correlation plane data, and a synthetic discriminant function-based nonlinear optical correlator. Other topics include an interactive optical-digital image processor, geometric transformations for video compression and human teleoperator display, quasiconformal remapping for compensation of human visual field defects, hybrid vision for automated spacecraft landing, advanced symbolic and inference optical correlation filters, and a rotationally invariant holographic tracking system. Additional topics include the detection of rotational and scale-varying objects with a programmable joint transform correlator, a single spatial light modulator binary nonlinear optical correlator, optical joint transform correlation, linear phase coefficient composite filters, and binary phase-only filters.

  2. Automatic recognition algorithm of cylindrical printing character%柱面喷码字符的自动识别算法

    Institute of Scientific and Technical Information of China (English)

    王学华; 王华龙; 马凡杰; 李安翼; 刘苏

    2015-01-01

    The character information about product ID wi11 be attached on the surfaces of a1most a11 of the products in the 1arge-sca1e industria1 production process, and the automatic co11ection and identification of product ID in the way of character recognition p1ays an important ro1e in the who1e 1ife cyc1e of the products. To meet the workshop working app1ications, the character recognition system must have the characteristics of rapid recognition speed, high identification efficiency and good robustness. Combined with advanced language programming,an automatic data collection and online recognition system for the information printed on the dylinder surface copper ring product was proposed based on MVTec HALCON machine vision platform. The proposed system includes parts automated de1ivery, image acquisition, information judgment and sorting, in which the prob1ems of image processing and optica1 character recognition(OCR) of characters with irregu1ar arrangement, distortion and b1ur on the cy1inder surface of copper ring was so1ved. The resu1t indicates that the recognition rate of the irregu1ar character information is up to 99%, and the integration of products pro-ducing and detecting process is rea1ized for the copper ring production.%在大规模工业生产过程中,几乎所有产品表面都会负载产品标示的字符信息。采取字符识别的方式对产品信息进行自动采集及判别在产品的整个生命周期中起着重要作用,因此满足工业现场工况要求的字符识别系统必须具备识别速度快,辨识效率高﹑鲁棒性好的特点。基于机器视觉平台MVTec HAL-CON,结合高级语言编程,设计和开发了铜环产品柱面喷码信息的自动采集及在线识别系统,包含物料输送﹑图像采集﹑信息判断及分拣,解决了工业铜环柱面不规则排列字符﹑扭曲变形字符和模糊字符信息的图像处理和OCR(Optica1 Character Recognition)字符识别问题。运行结果表明不规则字

  3. 双半字识别算法在水表字符识别系统中的应用%Application of Improved Double Half-word Recognition Method in Water Character Recognition System

    Institute of Scientific and Technical Information of China (English)

    徐平; 许彬; 常英杰

    2016-01-01

    In water character recognition system ,it is hard to recognize the character when upper and lower half‐word is incomplete because of the usual situation of partial carry caused by meter mechanical structure .To solve the problem ,an improved double half‐word recognition algorithm is proposed in this paper .Firstly ten standard complete two‐character templates are made .Then double half‐word is cut from the two‐character templates based on the incomplete double half‐word which is waited recognition by segmentation and the improved Hausdorff‐distance template matching is applied to pattern match .Finally the character is determined by comparing the ratio of upper and lower half ‐word .It approves that this improved algorithm shows good recognition to this type of double half ‐word and improves effectively the character recognition power of automatic reading meter system in the experiment .%水表自动抄表系统中,由于水表机械结构的原因,读数转盘常常出现进位不完全的情况,导致读数出现上下双半残缺字符,不利于识别。对这类双半字符进行研究,提出了改进的双半字识别算法。首先制作十个标准的完整双字符模板,然后根据分割的待识别双半残缺字符,从完整双字符模板中截取双半字符模板,利用改进的 Hausdorff 距离模板匹配进行匹配识别,最后通过比较上下半字符的比例确定字符读数。实验结果表明,算法对这类双半字符有较好的识别结果,有效地提高了水表自动抄表系统中字符识别能力。

  4. Text Recognition from an Image

    Directory of Open Access Journals (Sweden)

    Shrinath Janvalkar

    2014-04-01

    Full Text Available To achieve high speed in data processing it is necessary to convert the analog data into digital data. Storage of hard copy of any document occupies large space and retrieving of information from that document is time consuming. Optical character recognition system is an effective way in recognition of printed character. It provides an easy way to recognize and convert the printed text on image into the editable text. It also increases the speed of data retrieval from the image. The image which contains characters can be scanned through scanner and then recognition engine of the OCR system interpret the images and convert images of printed characters into machine-readable characters [8].It improving the interface between man and machine in many applications

  5. USING STROKE-BASED OR CHARACTER-BASED SELF-ORGANIZING MAPS IN THE RECOGNITION OF ONLINE, CONNECTED CURSIVE SCRIPT

    NARCIS (Netherlands)

    SCHOMAKER, L

    1993-01-01

    Comparisons are made between a number of stroke-based and character-based recognizers of connected cursive script. In both approaches a Kohonen self-organizing neural network is used as a feature-vector quantizer. It is found that a ''best match only'' character-based recognizer performs better than

  6. Identification of the Patterns of Chinese Character Recognition in Students with Learning Disabilities Requiring Tier-2 Support: A Rasch Analysis

    Science.gov (United States)

    Ho, Fuk-chuen; Yan, Zi

    2014-01-01

    This study investigates the Chinese reading patterns of students with learning disabilities (LD). The performances of students with LD in reading the three categories of Chinese characters were particularly analysed: regular, irregular, and pseudo-characters. Fifty-three students with LD in reading and 44 students without LD of Year 4 were…

  7. USING STROKE-BASED OR CHARACTER-BASED SELF-ORGANIZING MAPS IN THE RECOGNITION OF ONLINE, CONNECTED CURSIVE SCRIPT

    NARCIS (Netherlands)

    SCHOMAKER, L

    Comparisons are made between a number of stroke-based and character-based recognizers of connected cursive script. In both approaches a Kohonen self-organizing neural network is used as a feature-vector quantizer. It is found that a ''best match only'' character-based recognizer performs better than

  8. The time-course of lexical activation in Japanese morphographic word recognition: evidence for a character-driven processing model.

    Science.gov (United States)

    Miwa, Koji; Libben, Gary; Dijkstra, Ton; Baayen, Harald

    2014-01-01

    This lexical decision study with eye tracking of Japanese two-kanji-character words investigated the order in which a whole two-character word and its morphographic constituents are activated in the course of lexical access, the relative contributions of the left and the right characters in lexical decision, the depth to which semantic radicals are processed, and how nonlinguistic factors affect lexical processes. Mixed-effects regression analyses of response times and subgaze durations (i.e., first-pass fixation time spent on each of the two characters) revealed joint contributions of morphographic units at all levels of the linguistic structure with the magnitude and the direction of the lexical effects modulated by readers' locus of attention in a left-to-right preferred processing path. During the early time frame, character effects were larger in magnitude and more robust than radical and whole-word effects, regardless of the font size and the type of nonwords. Extending previous radical-based and character-based models, we propose a task/decision-sensitive character-driven processing model with a level-skipping assumption: Connections from the feature level bypass the lower radical level and link up directly to the higher character level.

  9. Identification of the Patterns of Chinese Character Recognition in Students with Learning Disabilities Requiring Tier-2 Support: A Rasch Analysis

    Science.gov (United States)

    Ho, Fuk-chuen; Yan, Zi

    2014-01-01

    This study investigates the Chinese reading patterns of students with learning disabilities (LD). The performances of students with LD in reading the three categories of Chinese characters were particularly analysed: regular, irregular, and pseudo-characters. Fifty-three students with LD in reading and 44 students without LD of Year 4 were…

  10. Optical Modulation Format Recognition in Stokes Space for Digital Coherent Receivers

    DEFF Research Database (Denmark)

    Borkowski, Robert; Zibar, Darko; Caballero Jambrina, Antonio;

    2013-01-01

    We report on a novel method for optical modulation format recognition based on Stokes parameters and variational expectation maximization algorithm. Discrimination among six different pol-muxed coherent modulation formats is successfully demonstrated in simulation and experiment....

  11. Stokes Space-Based Optical Modulation Format Recognition for Digital Coherent Receivers

    DEFF Research Database (Denmark)

    Borkowski, Robert; Zibar, Darko; Caballero Jambrina, Antonio

    2013-01-01

    We present a technique for modulation format recognition for heterogeneous reconfigurable optical networks. The method is based on Stokes space signal representation and uses a variational Bayesian expectation maximization machine learning algorithm. Differentiation between diverse common coheren...

  12. Towards events recognition in a distributed fiber-optic sensor system: Kolmogorov-Zurbenko filtering

    CERN Document Server

    Fedorov, Aleksey; Zhirnov, Andrey; Nesterov, Evgeniy; Namiot, Dmitry; Pnev, Alexey; Karasik, Valery

    2015-01-01

    The paper is about de-noising procedures aimed on events recognition in signals from a distributed fiber-optic vibration sensor system based on the phase-sensitive optical time-domain reflectometry. We report experimental results on recognition of several classes of events in a seismic background. A de-noising procedure uses the framework of the time-series analysis and Kolmogorov-Zurbenko filtering. We demonstrate that this approach allows revealing signatures of several classes of events.

  13. A Proposed Hybrid Technique for Recognizing Arabic Characters

    Directory of Open Access Journals (Sweden)

    S F Bahgat

    2012-07-01

    Full Text Available Optical character recognition systems improve human-machine interaction and are urgently required for many governmental and commercial departments. A considerable progress in the recognition techniques of Latin and Chinese characters has been achieved. By contrast, Arabic Optical Character Recognition (AOCR is still lagging although the interest and research in this area is becoming more intensive than before. This is because the Arabic is a cursive language, written from right to left, each character has two to four different forms according to its position in the word, and most characters are associated with complementary parts above, below, or inside the character. The process of Arabic character recognition passes through several stages; the most serious and error-prone of which are segmentation, and feature extraction & classification. This research focuses on the feature extraction and classification stage, being as important as the segmentation stage. Features can be classified into two categories; Local features, which are usually geometric, and Global features, which are either topological or statistical. Four approaches related to the statistical category are to be investigated, namely: Moment Invariants, Gray Level Co-occurrence Matrix, Run Length Matrix, and Statistical Properties of Intensity Histogram. The paper aims at fusing the features of these methods to get the most representative feature vector that maximizes the recognition rate.

  14. 对人脸识别特征数据降维算法的优化%Optimization of Dimension Reduction Algorithm for Face Recognition Character Data

    Institute of Scientific and Technical Information of China (English)

    杨玉平; 向华

    2012-01-01

    在模式识别领域,人脸特征数据相对庞大,为了提取人脸主要的特征数据,提高识别系统的运行效率,对特征数据的降维是必须的操作。针对现有降维算法对识别率有较大影响的问题,本文总结了各类降维算法,提出了一种优化的降维算法。%In the field of pattern recognition,facial character data is relatively large,and therefore it is necessary to reduce the dimension of the character data in order to extract the primary facial main data and improve the efficiency of the recognition system.For the existing dimension reduction algorithm has some negative effect on the recognition rate,this article sums up various kinds of dimension reduction algorithms and brings forward a better algorithm.

  15. Not all visual expertise is holistic, but it may be leftist: the case of Chinese character recognition.

    Science.gov (United States)

    Hsiao, Janet H; Cottrell, Garrison W

    2009-04-01

    We examined whether two purportedly face-specific effects, holistic processing and the left-side bias, can also be observed in expert-level processing of Chinese characters, which are logographic and share many properties with faces. Non-Chinese readers (novices) perceived these characters more holistically than Chinese readers (experts). Chinese readers had a better awareness of the components of characters, which were not clearly separable to novices. This finding suggests that holistic processing is not a marker of general visual expertise; rather, holistic processing depends on the features of the stimuli and the tasks typically performed on them. In contrast, results for the left-side bias were similar to those obtained in studies of face perception. Chinese readers exhibited a left-side bias in the perception of mirror-symmetric characters, whereas novices did not; this effect was also reflected in eye fixations. Thus, the left-side bias may be a marker of visual expertise.

  16. 基于Sherlock的光学字符识别%Optical Character Recognition Based on Sherlock

    Institute of Scientific and Technical Information of China (English)

    喻伟林; 郑苹

    2005-01-01

    产品外包装上印刷字符的自动识别是自动化生产线的一项重要功能,能够大幅度提高检测的自动化水平,提高生产效率.本文介绍基于Sherlock的光学字符识别系统的构成,说明Sherlock软件中的光学字符识别模块的功能,并结合实例说明在识别产品外包装上的点阵列和分段字符以及退化字符等方面的应用.

  17. Taking a radical position: Evidence for position specific radical representations in Chinese character recognition using masked priming ERP

    Directory of Open Access Journals (Sweden)

    I-Fan eSu

    2012-09-01

    Full Text Available In the investigation of orthographic representation of Chinese characters, one question that has stimulated much research is whether radicals (character components are specified for spatial position in a character (e.g. Ding, Peng, & Taft, 2004; Tsang & Chen, 2009. Differing from previous work, component or radical position information in this study is conceived in terms of relative frequency across different positions of characters containing it. A lexical decision task in a masked priming paradigm focusing on radicals with preferred position of occurrence was conducted. A radical position that encompasses more characters than other positions was identified to be the preferred position of a particular radical. The prime that was exposed for 96ms might share a radical with the target in the same or different positions. Moreover, the shared radical appeared either in its preferred or non-preferred position in the target. While response latencies only revealed the effect of graphical similarity, both effects of graphical similarity and radical position preference were found in the ERP results. The former effect was reflected in greater positivity in occipital P1 and greater negativity in N400 for radicals in different positions in prime and target characters. The latter effect manifested as greater negativity in occipital N170 and greater positivity in frontal P200 in the same time window elicited by radicals in their non-preferred position. Equally interesting was the reversal of the effect of radical position preference in N400 with greater negativity associated with radicals in preferred position. These findings identify the early ERP components associated with activation of position-specific radical representations in the orthographic lexicon, and reveal the change in the nature of competition from processing at the radical level to the lexical level.

  18. Taking a Radical Position: Evidence for Position-Specific Radical Representations in Chinese Character Recognition Using Masked Priming ERP.

    Science.gov (United States)

    Su, I-Fan; Mak, Sin-Ching Cassie; Cheung, Lai-Ying Milly; Law, Sam-Po

    2012-01-01

    In the investigation of orthographic representation of Chinese characters, one question that has stimulated much research is whether radicals (character components) are specified for spatial position in a character (e.g., Ding et al., 2004; Tsang and Chen, 2009). Differing from previous work, component or radical position information in this study is conceived in terms of relative frequency across different positions of characters containing it. A lexical decision task in a masked priming paradigm focusing on radicals with preferred position of occurrence was conducted. A radical position that encompasses more characters than other positions was identified to be the preferred position of a particular radical. The prime that was exposed for 96 ms might share a radical with the target in the same or different positions. Moreover, the shared radical appeared either in its preferred or non-preferred position in the target. While response latencies only revealed the effect of graphical similarity, both effects of graphical similarity and radical position preference were found in the event-related potential (ERP) results. The former effect was reflected in greater positivity in occipital P1 and greater negativity in N400 for radicals in different positions in prime and target characters. The latter effect manifested as greater negativity in occipital N170 and greater positivity in frontal P200 in the same time window elicited by radicals in their non-preferred position. Equally interesting was the reversal of the effect of radical position preference in N400 with greater negativity associated with radicals in preferred position. These findings identify the early ERP components associated with activation of position-specific radical representations in the orthographic lexicon, and reveal the change in the nature of competition from processing at the radical level to the lexical level.

  19. Semi-automatic ground truth generation using unsupervised clustering and limited manual labeling: Application to handwritten character recognition.

    Science.gov (United States)

    Vajda, Szilárd; Rangoni, Yves; Cecotti, Hubert

    2015-06-01

    For training supervised classifiers to recognize different patterns, large data collections with accurate labels are necessary. In this paper, we propose a generic, semi-automatic labeling technique for large handwritten character collections. In order to speed up the creation of a large scale ground truth, the method combines unsupervised clustering and minimal expert knowledge. To exploit the potential discriminant complementarities across features, each character is projected into five different feature spaces. After clustering the images in each feature space, the human expert labels the cluster centers. Each data point inherits the label of its cluster's center. A majority (or unanimity) vote decides the label of each character image. The amount of human involvement (labeling) is strictly controlled by the number of clusters - produced by the chosen clustering approach. To test the efficiency of the proposed approach, we have compared, and evaluated three state-of-the art clustering methods (k-means, self-organizing maps, and growing neural gas) on the MNIST digit data set, and a Lampung Indonesian character data set, respectively. Considering a k-nn classifier, we show that labeling manually only 1.3% (MNIST), and 3.2% (Lampung) of the training data, provides the same range of performance than a completely labeled data set would.

  20. REAL-TIME FACE RECOGNITION BASED ON OPTICAL FLOW AND HISTOGRAM EQUALIZATION

    Directory of Open Access Journals (Sweden)

    D. Sathish Kumar

    2013-05-01

    Full Text Available Face recognition is one of the intensive areas of research in computer vision and pattern recognition but many of which are focused on recognition of faces under varying facial expressions and pose variation. A constrained optical flow algorithm discussed in this paper, recognizes facial images involving various expressions based on motion vector computation. In this paper, an optical flow computation algorithm which computes the frames of varying facial gestures, and integrating with synthesized image in a probabilistic environment has been proposed. Also Histogram Equalization technique has been used to overcome the effect of illuminations while capturing the input data using camera devices. It also enhances the contrast of the image for better processing. The experimental results confirm that the proposed face recognition system is more robust and recognizes the facial images under varying expressions and pose variations more accurately.

  1. Recognition of multi-fontstyle characters based on convolutional neural network%基于卷积神经网络的多字体字符识别

    Institute of Scientific and Technical Information of China (English)

    吕刚

    2011-01-01

    By using the stochastic diagonal Levenberg-Marquardt method into convolutional network presented by Simard, it was analysed the relations between sample class number, global learning rate and network's convergence speed. Simard network was then extended to multi-fontstyle little character set such as Baidu CAP-TCHA. A recognition rate 98.4% in single Baidu CAPTCHA character, and 93. 5% as whole was reached. Experimental results confirmed that Simard network could be used in recogniton of mutli-fontstyle little character set.%采用随机对角Levenberg-Marquardt算法有效改进了Simard卷积网络的收敛速度,分析了样本类别数、全局学习率对网络收敛速度的影响,并成功地把Simard网络推广到对百度验证码等多字体小字符集的识别,达到98.4%的单字符识别率和93.5%的整体识别率.实验表明:改进后的Simard网络具有前期预处理少、泛化能力强、收敛速度较快的优点,可以胜任多字体小字符集的识别工作.

  2. Large pattern online handwriting character recognition based on multi-convolution neural network%基于多重卷积神经网络的大模式联机手写文字识别

    Institute of Scientific and Technical Information of China (English)

    葛明涛; 王小丽; 潘立武

    2014-01-01

    Online handwriting character recognition is an important field in the research of pattern recognition. The tradi-tional recognition method is based on the common convolutional neural networks(CNNs)technology. It has an efficient recogni-tion rate for the small pattern character set online handwriting characters,but has low recognition rate for the large pattern character set recognition. A recognition method based on multi-convolutional neural networks(MCNNs)is presented in this pa-per to overcome the situation that the previous methods have the low recognition rate for large pattern character set and improve the recognition rate for the large pattern handwriting character set recognition. The stochastic diagonal Levenbert-Marquardt meth-od is used in the system for training optimization. The experimental results show that the proposed method has the recognition rate of 89% and has a good prospect for online handwriting character recognition for large scale pattern.%联机手写识别在日常生产生活中有着广阔的应用,模式识别也一直把其作为研究的重点。传统的识别方法是利用普通卷积神经网络技术,该方法在对小规模字符集联机手写文字识别时有着较高识别率,总体性能高,但在对大规模字符集识别时,识别率则大大降低。提出一种基于多重卷积神经网络的识别方法,旨在克服以往方法对大规模字符集识别时识别效率不高的问题,提高大规模字符集联机手写文字的识别率。系统使用随机对角Levenberg-Marquardt方法来优化训练,通过使用UNIPEN训练集测试该方法识别准确率可达89%,是一个有良好前景的联机手写识别方法。

  3. On Chinese Characters in Meiji Japanese and Japanese Self-recognition%明治日本的汉字观与日本人的自我认识

    Institute of Scientific and Technical Information of China (English)

    韩冰

    2012-01-01

    汉字最初传到日本之时作为象征神圣与权威的事物被日本人民所崇拜。然而到了近代特别是明治时期以来众多的知识分子却提出了以废除汉字为主的汉字观,并开展了盛极一时的汉字废除运动。明治知识分子的这种汉字观是受国学者及水户学者的影响而发展起来的自国优越思想。明治时期的汉字认识过程实际上就是自我身份构建的过程,既自我认识的过程。%The Chinese character was considered as holy and authoritative thing worshipped by Japanese people when it was originally introduced into Japan. However, since modern times, especially Meiji Time, numerous Japanese intellectuals put forward a viewpoint on Chinese characters which focused on abolishing Chinese characters in Japanese and developed Chinese abolishment movement which prevailed for a long time. Influenced by Kokugaku scholars and Mito scholars, the intellectuals developed the viewpoint from the thoughts that Japan was superior to other countries. The process of Chinese recognition in Meiji Time was actually the process of identity construction, namely, the process of self-recognition.

  4. Hand Gesture Recognition Based on HOG Characters and SVM%基于HOG特征和SVM的手势识别

    Institute of Scientific and Technical Information of China (English)

    任彧; 顾成成

    2011-01-01

    手势识别具有比较丰富的应用领域,而领域的变化也会对识别的结果产牛较大的影响.在诸多手势识别方法中,基于计算机视觉的识别技术对环境最敏感,例如光线亮暗、复杂背景、手势旋转等.为克服环境带来的影响,借鉴了近年来在目标检测研究中应用较多的梯度方向直方图技术,将其用于手势识别中.这种方法使得基于视觉的手势识别对环境不再敏感,得到了较好的识别效果.%Hand gesture recognition has abundant application fields, and the change of fields will result great influence to the result of recognition.In all gesture recognition methods, the one which based on computer vision is most sensitive to environment, such as too bright or too dark light, complex background, hand gesture rotation, etc.In order to overcome the impact of environment, histograms of oriented gradient which is being used in target detection research widely is used in hand gesture recognition.This method makes hand gesture recognition based on computer vision be sensitive to environment no longer, and a good recognition effect has been achieved.

  5. Gabor filter based optical image recognition using Fractional Power Polynomial model based common discriminant locality preserving projection with kernels

    Science.gov (United States)

    Li, Jun-Bao

    2012-09-01

    This paper presents Gabor filter based optical image recognition using Fractional Power Polynomial model based Common Kernel Discriminant Locality Preserving Projection. This method tends to solve the nonlinear classification problem endured by optical image recognition owing to the complex illumination condition in practical applications, such as face recognition. The first step is to apply Gabor filter to extract desirable textural features characterized by spatial frequency, spatial locality and orientation selectivity to cope with the variations in illumination. In the second step we propose Class-wise Locality Preserving Projection through creating the nearest neighbor graph guided by the class labels for the textural features reduction. Finally we present Common Kernel Discriminant Vector with Fractional Power Polynomial model to reduce the dimensions of the textural features for recognition. For the performance evaluation on optical image recognition, we test the proposed method on a challenging optical image recognition problem, face recognition.

  6. Automated Mulitple Object Optical Tracking and Recognition System Project

    Data.gov (United States)

    National Aeronautics and Space Administration — OPTRA proposes to develop an optical tracking system that is capable of recognizing and tracking up to 50 different objects within an approximately 2 degree x 3...

  7. Computer Recognition of Facial Profiles

    Science.gov (United States)

    1974-08-01

    z30 o u u cr W, 137 REFERENCES 1. Fischer , C. L., Pollock, D. K., Raddack, B., and Stevens, M. E., Optical Character Recognition, Spartan Books...K. W., and Haworth , P. A., "Automatic Shape betectinn for Programmed Terrain Classifica-’ tion," Proc. Soc. Photographic Instrumentation Engrs

  8. Benchmark for license plate character segmentation

    Science.gov (United States)

    Gonçalves, Gabriel Resende; da Silva, Sirlene Pio Gomes; Menotti, David; Shwartz, William Robson

    2016-09-01

    Automatic license plate recognition (ALPR) has been the focus of many researches in the past years. In general, ALPR is divided into the following problems: detection of on-track vehicles, license plate detection, segmentation of license plate characters, and optical character recognition (OCR). Even though commercial solutions are available for controlled acquisition conditions, e.g., the entrance of a parking lot, ALPR is still an open problem when dealing with data acquired from uncontrolled environments, such as roads and highways when relying only on imaging sensors. Due to the multiple orientations and scales of the license plates captured by the camera, a very challenging task of the ALPR is the license plate character segmentation (LPCS) step, because its effectiveness is required to be (near) optimal to achieve a high recognition rate by the OCR. To tackle the LPCS problem, this work proposes a benchmark composed of a dataset designed to focus specifically on the character segmentation step of the ALPR within an evaluation protocol. Furthermore, we propose the Jaccard-centroid coefficient, an evaluation measure more suitable than the Jaccard coefficient regarding the location of the bounding box within the ground-truth annotation. The dataset is composed of 2000 Brazilian license plates consisting of 14000 alphanumeric symbols and their corresponding bounding box annotations. We also present a straightforward approach to perform LPCS efficiently. Finally, we provide an experimental evaluation for the dataset based on five LPCS approaches and demonstrate the importance of character segmentation for achieving an accurate OCR.

  9. Using Multidimensional ADTPE and SVM for Optical Modulation Real-Time Recognition

    Directory of Open Access Journals (Sweden)

    Junyu Wei

    2016-01-01

    Full Text Available Based on the feature extraction of multidimensional asynchronous delay-tap plot entropy (ADTPE and multiclass classification of support vector machine (SVM, we propose a method for recognition of multiple optical modulation formats and various data rates. We firstly present the algorithm of multidimensional ADTPE, which is extracted from asynchronous delay sampling pairs of modulated optical signal. Then, a multiclass SVM is utilized for fast and accurate classification of several widely-used optical modulation formats. In addition, a simple real-time recognition scheme is designed to reduce the computation time. Compared to the existing method based on asynchronous delay-tap plot (ADTP, the theoretical analysis and simulation results show that our recognition method can effectively enhance the tolerance of transmission impairments, obtaining relatively high accuracy. Finally, it is further demonstrated that the proposed method can be integrated in an optical transport network (OTN with flexible expansion. Through simply adding the corresponding sub-SVM module in the digital signal processer (DSP, arbitrary new modulation formats can be recognized with high recognition accuracy in a short response time.

  10. Elimination of character-resembling anomalies within a detected region using density-dependent reference point construction in an automated license plate recognition system

    Science.gov (United States)

    Chai, Hum Yan; Meng, Liang Kim; Mohamed, Hamam; Woon, Hon Hock; Lai, Khin Wee

    2016-11-01

    The problem of eliminating character-resembling blobs on a detected region in the plate detection stage of an automated license plate recognition system is addressed. The proposed method amplifies the slight differences between the noncharacter blobs (anomalies) and the character blobs (true signal) to enhance the tractability. This method postulates on two propositions: (1) the anomalies are usually located around the true signal and the suspected anomalies and (2) blobs should be given less emphasis in computing a reference point. The first proposition is based on prior knowledge and observation; the second proposition is based on the fact that a reference point that takes anomalies into account is contaminated and thus misleading. The gist of the method mainly focuses on the methodology to emphasize the blobs differently in accordance to their location in computing the reference point that approximates the representative value of true signal properties more accurately, thus giving the effect of amplifying the slight differences. The performance of the method is evaluated on both its capability and consistency in solving certain types of anomalies.

  11. Adaptive, optical, radial basis function neural network for handwritten digit recognition

    Science.gov (United States)

    Foor, Wesley E.; Neifeld, Mark A.

    1995-11-01

    An adaptive, optical, radial basis function classifier for handwritten digit recognition is experimentally demonstrated. We describe a spatially multiplexed system that incorporates an on-line adaptation of weights and basis function widths to provide robustness to optical system imperfections and system noise. The optical system computes the Euclidean distances between a 100-dimensional input vector and 198 stored reference patterns in parallel by using dual vector-matrix multipliers and a contrast-reversing spatial light modulator. Software is used to emulate an electronic chip that performs the on-line learning of the weights and basis function widths. An experimental recognition rate of 92.7% correct out of 300 testing samples is achieved with the adaptive training, versus 31.0% correct for nonadaptive training. We compare the experimental results with a detailed computer model of the system in order to analyze the influence of various noise sources on the system performance.

  12. Some methods of encoding simple visual images for use with a sparse distributed memory, with applications to character recognition

    Science.gov (United States)

    Jaeckel, Louis A.

    1989-01-01

    To study the problems of encoding visual images for use with a Sparse Distributed Memory (SDM), I consider a specific class of images- those that consist of several pieces, each of which is a line segment or an arc of a circle. This class includes line drawings of characters such as letters of the alphabet. I give a method of representing a segment of an arc by five numbers in a continuous way; that is, similar arcs have similar representations. I also give methods for encoding these numbers as bit strings in an approximately continuous way. The set of possible segments and arcs may be viewed as a five-dimensional manifold M, whose structure is like a Mobious strip. An image, considered to be an unordered set of segments and arcs, is therefore represented by a set of points in M - one for each piece. I then discuss the problem of constructing a preprocessor to find the segments and arcs in these images, although a preprocessor has not been developed. I also describe a possible extension of the representation.

  13. Role of a singlet diradical character in carbon nanomaterials: a novel hot spot for efficient nonlinear optical materials.

    Science.gov (United States)

    Muhammad, Shabbir; Nakano, Masayoshi; Al-Sehemi, Abdullah G; Kitagawa, Yasutaka; Irfan, Ahmad; Chaudhry, Aijaz R; Kishi, Ryohei; Ito, Soichi; Yoneda, Kyohei; Fukuda, Kotaro

    2016-10-27

    Carbon atoms have the potential to produce a variety of fascinating all-carbon structures with amazing electronic and mechanical properties. Over the last few decades, several efforts have been made using experimental and computational techniques to functionalize graphene, carbon nanotubes and fullerenes for potential use in modern hi-tech electronic, medicinal, optical and nonlinear optical (NLO) applications. Since photons replaced electrons as a carrier of information, the field of NLO material design has drawn immense interest in contemporary materials science. There have been several reports of bridging the gap between the exciting fields of carbon nanomaterials and NLO materials by functionalizing carbon nanomaterials for potential NLO applications. In contrast to previous reports of the design of third-order NLO materials using conventional closed-shell materials, a novel strategy using open-shell diradical molecular systems has recently been proposed. Quantum chemically, diradical character is explained in terms of the instability of the chemical bonds in open-shell molecular systems. Interestingly, several carbon nanomaterials, which naturally possess open-shell singlet configurations, have recently gained momentum in the design of these classes of open-shell NLO materials with excellent NLO properties, stability and diversity. The present review establishes a systematic sequence of different studies (spanning over two decades of intense research efforts), starting from the simplest theoretical two-site diradical model, continuing to its experimental and theoretical realization in actual chemical systems, and finally applying the abovementioned model/rule to novel carbon nanomaterials to tune their NLO properties, particularly their second hyperpolarizability (γ). In the present report, we highlight several recent efforts to functionalize carbon nanomaterials by exploiting their open-shell diradical character to achieve efficient third-order NLO

  14. Accuracy, security, and processing time comparisons of biometric fingerprint recognition system using digital and optical enhancements

    Science.gov (United States)

    Alsharif, Salim; El-Saba, Aed; Jagapathi, Rajendarreddy

    2011-06-01

    Fingerprint recognition is one of the most commonly used forms of biometrics and has been widely used in daily life due to its feasibility, distinctiveness, permanence, accuracy, reliability, and acceptability. Besides cost, issues related to accuracy, security, and processing time in practical biometric recognition systems represent the most critical factors that makes these systems widely acceptable. Accurate and secure biometric systems often require sophisticated enhancement and encoding techniques that burdens the overall processing time of the system. In this paper we present a comparison between common digital and optical enhancementencoding techniques with respect to their accuracy, security and processing time, when applied to biometric fingerprint systems.

  15. Neural networks for the optical recognition of defects in cloth

    Science.gov (United States)

    Hoffer, Lois M.; Francini, Franco; Tiribilli, Bruno; Longobardi, Giuseppe

    1996-11-01

    A fast system to reveal the presence and type of fabric defects during the weaving process is developed. Since the fabric is similar to a 2D grid, its defects are clearly observed in the changes in its optical Fourier transform (OFT), which appears stationary while the fabric is moving across the loom. Previous work, based on the statistical parameters of the OFT, showed that the presence of faults can be detected when only global changes in the images are considered. We show that by selecting a small subset of pixels from the image as input to a neural network, fabric defects can not only be detected but also successfully identified. A knowledge-based system could conceivably be constructed to use this information to resolve problems with the loom in real time, without the need for operator intervention.

  16. Document recognition serving people with disabilities

    Science.gov (United States)

    Fruchterman, James R.

    2007-01-01

    Document recognition advances have improved the lives of people with print disabilities, by providing accessible documents. This invited paper provides perspectives on the author's career progression from document recognition professional to social entrepreneur applying this technology to help people with disabilities. Starting with initial thoughts about optical character recognition in college, it continues with the creation of accurate omnifont character recognition that did not require training. It was difficult to make a reading machine for the blind in a commercial setting, which led to the creation of a nonprofit social enterprise to deliver these devices around the world. This network of people with disabilities scanning books drove the creation of Bookshare.org, an online library of scanned books. Looking forward, the needs for improved document recognition technology to further lower the barriers to reading are discussed. Document recognition professionals should be proud of the positive impact their work has had on some of society's most disadvantaged communities.

  17. Topographic Feature Extraction for Bengali and Hindi Character Images

    CERN Document Server

    Bag, Soumen; 10.5121/sipij.2011.2215

    2011-01-01

    Feature selection and extraction plays an important role in different classification based problems such as face recognition, signature verification, optical character recognition (OCR) etc. The performance of OCR highly depends on the proper selection and extraction of feature set. In this paper, we present novel features based on the topography of a character as visible from different viewing directions on a 2D plane. By topography of a character we mean the structural features of the strokes and their spatial relations. In this work we develop topographic features of strokes visible with respect to views from different directions (e.g. North, South, East, and West). We consider three types of topographic features: closed region, convexity of strokes, and straight line strokes. These features are represented as a shape-based graph which acts as an invariant feature set for discriminating very similar type characters efficiently. We have tested the proposed method on printed and handwritten Bengali and Hindi...

  18. Automatic fishing net detection and recognition based on optical gated viewing for underwater obstacle avoidance

    Science.gov (United States)

    Liu, Xiaoquan; Wang, Xinwei; Ren, Pengdao; Cao, Yinan; Zhou, Yan; Liu, Yuliang

    2017-08-01

    An automatic fishing net detection and recognition method for underwater obstacle avoidance is proposed. In the method, optical gated viewing technology is utilized to obtain high-resolution fishing net images and extend detection distance by suppressing water backscattering and background noise. The fishing net recognition is based on the proposed histograms of slope lines (HSLs) descriptors plus a support vector machine classifier. The extraction of HSL descriptors includes five steps of contrast-limited adaptive histogram equalization, the Gaussian low-pass filtering, the Canny detection, the Hough transform, and weighted vote. In the proof experiments, the detection distance of the fishing net reaches 5.7 attenuation length and the recognition accuracy reaches 93.79%.

  19. Optical characters and texture maps of skin and the aging mechanism by use of multiphoton microscopy and optical coherence tomography

    Science.gov (United States)

    Wu, Shulian; Li, Hui; Zhang, Xiaoman; Huang, Yudian; Xu, Xiaohui

    2012-03-01

    Cutaneous aging is a complicated biological process affecting different constituents of skin, which can be divided into two types: the chronological aging and the photo-aging. The two cutaneous aging processes often co-exist accompanying with each other. The effects are often overlapped including changes in epithelium and dermis. The degeneration of collagen is a major factor in dermal alteration with aging. In this study, multiphoton microscopy (MPM) with its high resolution imaging and optical coherence tomography (OCT) with its depth resolved imaging were used to study the anti-aging dermatology in vivo. It was attempted to make the optical parameter and texture feature to evaluate the process of aging skin using mathematical image processing. The links among optical parameter, spectrum and texture feature in collagen with aging process were established to uncover mechanism of aging skin.

  20. Development of Biological Movement Recognition by Interaction between Active Basis Model and Fuzzy Optical Flow Division

    Directory of Open Access Journals (Sweden)

    Bardia Yousefi

    2014-01-01

    Full Text Available Following the study on computational neuroscience through functional magnetic resonance imaging claimed that human action recognition in the brain of mammalian pursues two separated streams, that is, dorsal and ventral streams. It follows up by two pathways in the bioinspired model, which are specialized for motion and form information analysis (Giese and Poggio 2003. Active basis model is used to form information which is different from orientations and scales of Gabor wavelets to form a dictionary regarding object recognition (human. Also biologically movement optic-flow patterns utilized. As motion information guides share sketch algorithm in form pathway for adjustment plus it helps to prevent wrong recognition. A synergetic neural network is utilized to generate prototype templates, representing general characteristic form of every class. Having predefined templates, classifying performs based on multitemplate matching. As every human action has one action prototype, there are some overlapping and consistency among these templates. Using fuzzy optical flow division scoring can prevent motivation for misrecognition. We successfully apply proposed model on the human action video obtained from KTH human action database. Proposed approach follows the interaction between dorsal and ventral processing streams in the original model of the biological movement recognition. The attained results indicate promising outcome and improvement in robustness using proposed approach.

  1. Optical implementation of a feature-based neural network with application to automatic target recognition

    Science.gov (United States)

    Chao, Tien-Hsin; Stoner, William W.

    1993-01-01

    An optical neural network based on the neocognitron paradigm is introduced. A novel aspect of the architecture design is shift-invariant multichannel Fourier optical correlation within each processing layer. Multilayer processing is achieved by feeding back the ouput of the feature correlator interatively to the input spatial light modulator and by updating the Fourier filters. By training the neural net with characteristic features extracted from the target images, successful pattern recognition with intraclass fault tolerance and interclass discrimination is achieved. A detailed system description is provided. Experimental demonstrations of a two-layer neural network for space-object discrimination is also presented.

  2. ERP Effect of Twirled Chinese Characters in Low Frequency Word Recognition%畸变汉字语义启动的ERP效应

    Institute of Scientific and Technical Information of China (English)

    舒德华; 王权红

    2012-01-01

    运用事件相关电位技术,采用词汇判断作业,考察字形畸变和语境对低频汉字识别的影响.行为结果显示,启动效应的主效应显著,启动条件和字形畸变的交互作用显著.脑电结果显示,150-300ms窗口,字形畸变的主效应显著.300-450ms时间窗口,启动效应的主效应显著.靶字畸变和靶字清晰条件下,均得到了语义相关和语义无关条件的显著差异.得出结论,汉字通透性是影响汉字加工的重要因素.RP与视知觉分析有关,N400和语义的自动加工有关.%In use of ERP technique, the present study invstigated the effects of twirled Chinese characters and semantic priming in low frequency word recognition. Twenty native Chinese undergraduates from Southwest University participated in the experiment during which they were instructed to make a yes\

  3. Structure, optical and thermal decomposition characters of LDPE graft copolymers synthesized by gamma irradiation

    Indian Academy of Sciences (India)

    M Madani

    2010-02-01

    Methyl methacrylate (MMA) monomer was grafted onto low density polyethylene by the direct method of radiation grafting. The effect of cohesive energy density of different organic solvents on the degree of grafting was investigated. It was found that the extent of grafting depends largely on the kind of solvent, in which the highest degree of grafting was achieved in the presence of dioxane, whereas the lowest degree of grafting occurred in the presence of methanol. This behaviour was attributed to the solubility parameters of the solvent, monomer and polymer. The change in structure of the LDPE graft copolymer films was characterized by scanning electron microscopy, X-ray diffraction, UV/vis absorption and thermogravimetric analysis. The X-ray diffraction results showed a decrease in the crystallinity of LDPE graft copolymer matrix at high degree of grafting. Studies were made on the UV-absorption edge, and indirect allowed transitions with their optical energy gaps are determined. At the same time the Urbach energy was evaluated. The activation energy of the thermal decomposition was calculated according to Horowitz and Metzger method.

  4. A high-speed readout scheme for fast optical correlation-based pattern recognition

    Science.gov (United States)

    McDonald, Gregor J.; Lewis, Meirion F.; Wilson, Rebecca

    2004-12-01

    We describe recent developments to a novel form of hybrid electronic/photonic correlator, which exploits component innovations in both electronics and photonics to provide fast, compact and rugged target recognition, applicable to a wide range of security applications. The system benefits from a low power, low volume, optical processing core which has the potential to realise man portable pattern recognition for a wide range of security based imagery and target databases. In the seminal Vander Lugt correlator the input image is Fourier transformed optically and multiplied optically with the conjugate Fourier transform of a reference pattern; the required correlation function is completed by taking the inverse Fourier transform of the product optically. The correlator described here is similar in principle, but performs the initial Fourier transforms and multiplication electronically, with only the final most computationally demanding output Fourier transform being performed optically. In this scheme the Fourier transforms of both the input scene and reference pattern are reduced to a binary phase-only format, where the multiplication process simplifies to a simple Boolean logic XOR function. The output of this XOR gate is displayed on a state-of-the-art Fast Bit Plane Spatial Light Modulator (FBPSLM). A novel readout scheme has been developed which overcomes the previous system output bottleneck and for the first time allows correlation frame readout rates capable of matching the inherently fast nature of the SLM. Readout rates of up to ~1 MHz are now possible, exceeding current SLM capabilities and meeting potential medium term SLM developments promised by SLMs based on novel materials and architectures.

  5. Nanomechanical recognition of prognostic biomarker suPAR with DVD-ROM optical technology

    DEFF Research Database (Denmark)

    Bache, Michael; Bosco, Filippo; Brøgger, Anna Line

    2013-01-01

    In this work the use of a high-throughput nanomechanical detection system based on a DVD-ROM optical drive and cantilever sensors is presented for the detection of urokinase plasminogen activator receptor inflammatory biomarker (uPAR). Several large scale studies have linked elevated levels...... of soluble uPAR (suPAR) to infectious diseases, such as HIV, and certain types of cancer. Using hundreds of cantilevers and a DVD-based platform, cantilever deflection response from antibody–antigen recognition is investigated as a function of suPAR concentration. The goal is to provide a cheap and portable...

  6. 基于权系数标识符矩阵的车牌字符识别方法%License plate character recognition based on weight coefficient identifier matrix

    Institute of Scientific and Technical Information of China (English)

    李志敏; 籍美苹; 薛平; 戴高; 谢仙宝

    2013-01-01

    为了提高对车牌字符的准确识别能力,提出了一种基于权系数标识符矩阵的模板匹配车牌字符识别方法。具体方法是在进行字符识别前为每一个车牌字符制定一个标准化的模板,再将每一个模板字符的像素依据像素区域、像素边缘区域和非像素及非像素边缘区域等标记成不同的区域,并依此为基准生成一个模板矩阵。根据车牌字符闭合区域个数及字符二值图像中间行、中间列黑白跳变次数,可将字符分为10类。进行字符识别时,首先判定待识别字符属于哪一类,然后与所在类的每一个字符的标准模板进行匹配,统计待识别字符落在每一个标准模板矩阵的不同区域的像素数,并根据不同区域的不同权值计算相似度值,相似度值最大的即为识别结果。该方法采用两级分类法对车牌字符图像进行分类,再采用基于权系数标识符矩阵的模板匹配法对车牌字符进行识别。实验结果表明,该方法提高了识别结果的准确度,对于存在字符断裂以及形状相似而容易混淆的字符有较好的识别效果。%In order to improve the accuracy of license plate recognition,a license plate character recognition method matching with a template based on weight coefficient identifier matrix is proposed. The specific method is to develop a standardized tem-plate for each license plate character before character recognition. Each standard template character is divided into three parts:pixel area,pixel edge region,non pixel and non-pixel edge region,which is taken as a criterion to generate a template matrix. According to the black-to-white jump times of number and character binary image in the middle row and middle line,the quanti-ty of pixles which drops down on different areas of each standardized template matrix from characters under recognition is count-ed. The similarity value depends on the weights on the area is

  7. Automated alignment system for optical wireless communication systems using image recognition.

    Science.gov (United States)

    Brandl, Paul; Weiss, Alexander; Zimmermann, Horst

    2014-07-01

    In this Letter, we describe the realization of a tracked line-of-sight optical wireless communication system for indoor data distribution. We built a laser-based transmitter with adaptive focus and ray steering by a microelectromechanical systems mirror. To execute the alignment procedure, we used a CMOS image sensor at the transmitter side and developed an algorithm for image recognition to localize the receiver's position. The receiver is based on a self-developed optoelectronic integrated chip with low requirements on the receiver optics to make the system economically attractive. With this system, we were able to set up the communication link automatically without any back channel and to perform error-free (bit error rate <10⁻⁹) data transmission over a distance of 3.5 m with a data rate of 3 Gbit/s.

  8. 印刷体汉字识别后处理方法的研究%Post-Processing Approach for Printed Chinese Character Recognition

    Institute of Scientific and Technical Information of China (English)

    张宏涛; 龙翀; 朱小燕; 孙俊

    2009-01-01

    高阶N-gram语言模型在OCR后处理方面有着广泛的应用,但也面临着因模型复杂度大导致的数据稀疏,以及耗费较多的时空资源等问题.该文针对印刷体汉字识别的后处理,提出了一种基于字节的语言模型的后处理算法.通过采用字节作为语言模型的基本表示单位,模型的复杂度大大降低,从而数据稀疏问题得到很大程度上缓解.实验证明,采用基于字节的语言模型的后处理系统能够以极少的时空开销获取很好的识别性能.在有部分分割错误的测试集上,正确率从88.67%提高到了98.32%,错误率下降了85.18%,运行速度较基于字以及基于词的系统有了大幅的提升,提高了后处理系统的综合性能;与目前常用的基于词的语言模型后处理系统相比,新系统能够节省95%的运行时间和98%的内存资源,但系统识别率仅降低了1.11%.%In Chinese OCR post-processing, the high-order Chinese n-gram language models, such as word based tri-gram and four-gram is still a challenging issue because of the data sparseness issue and large memory cost led by big model size. In this paper, we focus on the post-processing of printed Chinese character recognition and propose a byte-based language model. By choosing byte as the representing unit of language model, we achieve a remarkable reduction of model size which overcomes the sparseness problem to a great extent. The experimental results show that the new language model based on byte works very well with higher performance and lowest time and space costs. For the test set with segmentation errors, the recognition accuracy increases from 88. 67% to 98. 32% , which means 85. 18% error reduction. Compared with the system using traditional word based tri-gram, the new system saves 95% time cost and nearly 98% memory cost at almost no cost in the accuracy performance.

  9. 基于像素比例法和GA-BP的单相电表读数识别%Recognition of numeric characters on single-phase ammeter dial plate based on GA-BP and pixel-scale algorithms

    Institute of Scientific and Technical Information of China (English)

    冯冬青; 付巍; 石成辉

    2009-01-01

    对单相电表表盘读数的显示特点进行了研究,针对在电表表盘末位刻度识别中存在识别困难,识别率低的情况,提出了像素比例法这一精确识别方法.对初始图像采用大津二值化法,中值滤波法进行预处理,用投影法分别对字段及单个字符进行分割.采用GA-BP算法识别表盘读数.在样本集下单整字识别率为99.2%,非整字识别率为97.7%.实验结果表明,该方法对刻度有较高的识别精度.%The feature is researched, which numeric characters display on single-phase ammeter dial plate. Against the scale which is on the bottom of the ammeter dial plate is difficult to be recognized, and its recognition rate is very low, an algorithm based on Pixei-scale method is put forward. Otsu binary transform algorithm and mid-value filter method are used to preprocess the original image. Pro-jection algorithm is used to field a single character and the segmentation. GA-BP algorithm is introduced into precise automatic recognition of numeric characters on single-phase ammeter dial plate. The whole-word recognition rate reaches 99.2%, non-whole word recognition rate reaches 97.7%. Experiments show that the algorithm has more high precision.

  10. 维吾尔新文字印刷体识别系统的研究与开发%Research and Development of a Printed Uighur New Writing Character Recognition System

    Institute of Scientific and Technical Information of China (English)

    邹霞; 哈力木拉提·买买提; 艾尔肯·赛甫丁

    2012-01-01

    通过深入分析维吾尔新文字印刷体的特征,提出并建立了新文字识别系统原型.系统利用积分投影法从文本图像中分离出单个字符,提取字符的多种特征,结合模板匹配和特征匹配的方法进行识别,结果证明,这些方法对维吾尔新文字印刷体的识别得到了比较满意的结果.%Uighur new writing has been widely used in the Xinjiang Uygur Autonomous Region. Through an in-depth study of the characteristics of the Uighur new writing, the authors proposed and implemented the printed Uighur new writing character recognition system prototype. The system utilizes an integral projection method to separate the single characters from text image, extracts a variety of features, and combines with the template matching and the feature matching methods to recognize. The experimental results indicate that these methods to make the printed Uighur new writing character recognition system had a comparative satisfying result.

  11. 郁达夫对日本文化和日本国民性的认识%Yu Dafu's Recognition of Japanese Culture and Japanese National Character

    Institute of Scientific and Technical Information of China (English)

    许宪国

    2012-01-01

    Yu Dafu's recognition of Japanese culture and Japanese national character from the early favor of Japanese culture and sad telling about weak people to rational evaluation of Japanese culture and Japanese national character in 1930s includs a tangle of love and hate feelings. He takes Japan as a reference to China~s national culture and national characters, and then makes criticism on them, which is just a miniature of the recognition of Japan of the Chinese who studied in Japan in Meiji Taisho Period.%郁达夫对日本文化和日本国民性的认识从早期对日本文化的喜爱和弱国子民的悲哀诉说到20世纪30年代对日本文化和国民性的理性评价,包含着爱与憎的感情纠结。他以日本为镜子参照本民族文化和国民性,进而对之进行批判,这正是明治大正时期留学日本的一代中国人认识日本的缩影。

  12. Robust modulation formats recognition technique using wavelet transform for high speed optical networks

    Science.gov (United States)

    Guesmi, Latifa; Hraghi, Abir; Menif, Mourad

    2015-09-01

    There is a need, for high speed optical communication networks, in the monitoring process, to determine the modulation format type of a received signal. In this paper, we present a new achievement of modulation format recognition technique, where we proposed the use of wavelet transform of the detected signal in conjunction with the artificial neural network (ANN) algorithm. Besides, wavelet transform is one of the most popular candidates of the time-frequency transformations, where the wavelets are generated from a basic wavelet function by dilations and translations. We proved that this technique is capable of recognizing the multi-carriers modulation scheme with high accuracy under different transmission impairments such as chromatic dispersion (CD), differential group delay (DGD) and accumulated amplified spontaneous emission (ASE) noise with different ranges. Both the theoretical analysis and the simulation results showed that the wavelet transform not only can be used for modulation identification of optical communication signals, but also has a better classification accuracies under appropriate OSNR (optical signal-to-noise ratio) values.

  13. BanglaLekha-Isolated: A multi-purpose comprehensive dataset of Handwritten Bangla Isolated characters

    Directory of Open Access Journals (Sweden)

    Mithun Biswas

    2017-06-01

    Full Text Available BanglaLekha-Isolated, a Bangla handwritten isolated character dataset is presented in this article. This dataset contains 84 different characters comprising of 50 Bangla basic characters, 10 Bangla numerals and 24 selected compound characters. 2000 handwriting samples for each of the 84 characters were collected, digitized and pre-processed. After discarding mistakes and scribbles, 1,66,105 handwritten character images were included in the final dataset. The dataset also includes labels indicating the age and the gender of the subjects from whom the samples were collected. This dataset could be used not only for optical handwriting recognition research but also to explore the influence of gender and age on handwriting. The dataset is publicly available at https://data.mendeley.com/datasets/hf6sf8zrkc/2.

  14. BanglaLekha-Isolated: A multi-purpose comprehensive dataset of Handwritten Bangla Isolated characters.

    Science.gov (United States)

    Biswas, Mithun; Islam, Rafiqul; Shom, Gautam Kumar; Shopon, Md; Mohammed, Nabeel; Momen, Sifat; Abedin, Anowarul

    2017-06-01

    BanglaLekha-Isolated, a Bangla handwritten isolated character dataset is presented in this article. This dataset contains 84 different characters comprising of 50 Bangla basic characters, 10 Bangla numerals and 24 selected compound characters. 2000 handwriting samples for each of the 84 characters were collected, digitized and pre-processed. After discarding mistakes and scribbles, 1,66,105 handwritten character images were included in the final dataset. The dataset also includes labels indicating the age and the gender of the subjects from whom the samples were collected. This dataset could be used not only for optical handwriting recognition research but also to explore the influence of gender and age on handwriting. The dataset is publicly available at https://data.mendeley.com/datasets/hf6sf8zrkc/2.

  15. Criteria for pathology recognition in optical coherence tomography of fallopian tubes

    Science.gov (United States)

    Kirillin, Mikhail; Panteleeva, Olga; Yunusova, Ekaterina; Donchenko, Ekaterina; Shakhova, Natalia

    2012-08-01

    An increase of infertility and chronic pelvic pains syndrome, a growing level of latent diseases of this group, as well as a stably high percentage (up to 25% for infertility and up to 60% for the chronic pelvic pains syndrome) of undetermined origin raises the requirement for novel introscopic diagnostic techniques. We demonstrate abilities of optical coherence tomography (OCT) as a complementary technique to laparoscopy in diagnostics of fallopian tubes pathologies. We have acquired OCT images of different parts of fallopian tubes in norm and with morphologically proven pathology. Based on comparative analysis of the OCT data and the results of histological studies, we have worked out the subjective OCT criteria for distinguishing between unaltered and pathologic tissues. The developed criteria are verified in blind recognition tests. Diagnostic efficacy of OCT diagnostics in the case ofpelvic inflammatory diseases has been statistically evaluated, and high diagnostic accuracy (88%) is shown. Basing of the subjective criteria, an attempt to develop independent criteria aimed for automated recognition of pathological states in fallopian tubes is undertaken. Enhanced diagnostic accuracy (96%) of the developed independent criteria is demonstrated.

  16. Design of coupled mace filters for optical pattern recognition using practical spatial light modulators

    Science.gov (United States)

    Rajan, P. K.; Khan, Ajmal

    1993-01-01

    Spatial light modulators (SLMs) are being used in correlation-based optical pattern recognition systems to implement the Fourier domain filters. Currently available SLMs have certain limitations with respect to the realizability of these filters. Therefore, it is necessary to incorporate the SLM constraints in the design of the filters. The design of a SLM-constrained minimum average correlation energy (SLM-MACE) filter using the simulated annealing-based optimization technique was investigated. The SLM-MACE filter was synthesized for three different types of constraints. The performance of the filter was evaluated in terms of its recognition (discrimination) capabilities using computer simulations. The correlation plane characteristics of the SLM-MACE filter were found to be reasonably good. The SLM-MACE filter yielded far better results than the analytical MACE filter implemented on practical SLMs using the constrained magnitude technique. Further, the filter performance was evaluated in the presence of noise in the input test images. This work demonstrated the need to include the SLM constraints in the filter design. Finally, a method is suggested to reduce the computation time required for the synthesis of the SLM-MACE filter.

  17. Recognition of Similar Handwritten Chinese Characters Based on CNN and Random Elastic Deformation%基于CNN和随机弹性形变的相似手写汉字识别

    Institute of Scientific and Technical Information of China (English)

    高学; 王有旺

    2014-01-01

    In order to recognize similar handwritten Chinese characters effectively,a convolutional neural network (CNN)model is proposed,and the topology of the network model is presented.Then,the sample set is extended by introducing a stochastic elastic deformation to enhance the generalization performance of the model.Experimen-tal results indicate that the recognition accuracy of the proposed CNN model is 1.66%higher than that of the tradi-tional CNN model,especially,for distorted handwritten Chinese characters,the recognition accuracy increases by 12.85%;moreover,as compared with the traditional recognition methods,the proposed CNN model reduces the recognition error rate by 36.47%.It is thus concluded that the proposed method is effective.%针对手写汉字中相似汉字的识别问题,构建了一种卷积神经网络(CNN)模型,并给出了其网络拓扑结构,通过随机弹性形变对样本集进行扩展,以提高模型的泛化性能.相似手写汉字的识别实验结果表明:相对于常规的CNN模型,文中CNN模型的手写汉字识别正确率提高1.66%,特别是对于变形的手写汉字,识别正确率提高12.85%;相对于传统的手写汉字识别方法,文中方法的识别错误率降低36.47%,从而验证了文中识别方法的有效性.

  18. Differential characters

    CERN Document Server

    Bär, Christian

    2014-01-01

    Providing a systematic introduction to differential characters as introduced by Cheeger and Simons, this text describes important concepts such as fiber integration, higher dimensional holonomy, transgression, and the product structure in a geometric manner. Differential characters form a model of what is nowadays called differential cohomology, which is the mathematical structure behind the higher gauge theories in physics.  

  19. Fuzzy Logic Module of Convolutional Neural Network for Handwritten Digits Recognition

    Science.gov (United States)

    Popko, E. A.; Weinstein, I. A.

    2016-08-01

    Optical character recognition is one of the important issues in the field of pattern recognition. This paper presents a method for recognizing handwritten digits based on the modeling of convolutional neural network. The integrated fuzzy logic module based on a structural approach was developed. Used system architecture adjusted the output of the neural network to improve quality of symbol identification. It was shown that proposed algorithm was flexible and high recognition rate of 99.23% was achieved.

  20. ZONING DESIGN FOR HAND­WRITTEN NUMERAL RECOGNITION

    NARCIS (Netherlands)

    Lecce Di, V.; Dimauro, G.; Guerriero, A.; Impedovo, S.; Pirlo, G.; Salzo, A.

    2004-01-01

    In the field of Optical Character Recognition (OCR), zoning is used to extract topological information from patterns. In this paper zoning is considered as the result of an optimisation problem and a new technique is presented for automatic zoning. More precisely, local analysis of feature distribut

  1. Practical automatic Arabic license plate recognition system

    Science.gov (United States)

    Mohammad, Khader; Agaian, Sos; Saleh, Hani

    2011-02-01

    Since 1970's, the need of an automatic license plate recognition system, sometimes referred as Automatic License Plate Recognition system, has been increasing. A license plate recognition system is an automatic system that is able to recognize a license plate number, extracted from image sensors. In specific, Automatic License Plate Recognition systems are being used in conjunction with various transportation systems in application areas such as law enforcement (e.g. speed limit enforcement) and commercial usages such as parking enforcement and automatic toll payment private and public entrances, border control, theft and vandalism control. Vehicle license plate recognition has been intensively studied in many countries. Due to the different types of license plates being used, the requirement of an automatic license plate recognition system is different for each country. [License plate detection using cluster run length smoothing algorithm ].Generally, an automatic license plate localization and recognition system is made up of three modules; license plate localization, character segmentation and optical character recognition modules. This paper presents an Arabic license plate recognition system that is insensitive to character size, font, shape and orientation with extremely high accuracy rate. The proposed system is based on a combination of enhancement, license plate localization, morphological processing, and feature vector extraction using the Haar transform. The performance of the system is fast due to classification of alphabet and numerals based on the license plate organization. Experimental results for license plates of two different Arab countries show an average of 99 % successful license plate localization and recognition in a total of more than 20 different images captured from a complex outdoor environment. The results run times takes less time compared to conventional and many states of art methods.

  2. TOPOGRAPHIC FEATURE EXTRACTION FOR BENGALI AND HINDI CHARACTER IMAGES

    Directory of Open Access Journals (Sweden)

    Soumen Bag

    2011-06-01

    Full Text Available Feature selection and extraction plays an important role in different classification based problems such as face recognition, signature verification, optical character recognition (OCR etc. The performance of OCR highly depends on the proper selection and extraction of feature set. In this paper, we present novel features based on the topography of a character as visible from different viewing directions on a 2D plane. By topography of a character we mean the structural features of the strokes and their spatial relations. In this work we develop topographic features of strokes visible with respect to views from different directions (e.g. North, South, East, and West. We consider three types of topographic features: closed region, convexity of strokes, and straight line strokes. These features are represented as a shapebased graph which acts as an invariant feature set for discriminating very similar type characters efficiently. We have tested the proposed method on printed and handwritten Bengali and Hindi character images. Initial results demonstrate the efficacy of our approach.

  3. Topographic Feature Extraction for Bengali and Hindi Character Images

    Directory of Open Access Journals (Sweden)

    Soumen Bag

    2011-09-01

    Full Text Available Feature selection and extraction plays an important role in different classification based problems such as face recognition, signature verification, optical character recognition (OCR etc. The performance of OCR highly depends on the proper selection and extraction of feature set. In this paper, we present novel features based on the topography of a character as visible from different viewing directions on a 2D plane. By topography of a character we mean the structural features of the strokes and their spatial relations. In this work we develop topographic features of strokes visible with respect to views from different directions (e.g. North, South, East, and West. We consider three types of topographic features: closed region, convexity of strokes, and straight line strokes. These features are represented as a shapebased graph which acts as an invariant feature set for discriminating very similar type characters efficiently. We have tested the proposed method on printed and handwritten Bengali and Hindi character images. Initial results demonstrate the efficacy of our approach.

  4. Research on a phased license plate character recognition algorithm based on neural network%基于神经网络的分阶车牌字符识别算法研究

    Institute of Scientific and Technical Information of China (English)

    李珊珊; 李一民; 郭真真

    2016-01-01

    In order to increase the license plate recognition rate and recognition speed in complex en-vironments, a phased license plate recognition algorithm based on BP neural network and convolution neural network( CNN) is proposed. This method BP neural network used to recognize license plate charac-ters, non-similar letters and numbers in the first stage;and improved CNN used to identify similar license plate letters and numbers in the second stage. Finally through the experimental results of vertical and hor-izontal comparison, the advantage of this method is obtained. Experimental results show that compared with other algorithms such as BP neural network, this method has improved the recognition rate while the recognition time is reduced.%为了提高复杂环境下车牌字符的识别率和识别速度,提出了一种基于BP神经网络和卷积神经网络( CNN)的分阶车牌字符识别算法。该算法第一阶段采用BP神经网络对车牌中的汉字、非相似字符进行识别;并在第二阶段用改进的CNN对车牌中的相似字符进行识别。最后通过实验横向、纵向对比,验证了该神经网络算法的有效性。实验结果表明,相对于传统的BP神经网络算法,明显提高了车牌字符的识别率,同时减少了车牌的识别时间。

  5. Vehicle License Plate Recognition Syst

    Directory of Open Access Journals (Sweden)

    Meenakshi,R. B. Dubey

    2012-12-01

    Full Text Available The vehicle license plate recognition system has greater efficiency for vehicle monitoring in automatic zone access control. This Plate recognition system will avoid special tags, since all vehicles possess a unique registration number plate. A number of techniques have been used for car plate characters recognition. This system uses neural network character recognition and pattern matching of characters as two character recognition techniques. In this approach multilayer feed-forward back-propagation algorithm is used. The performance of the proposed algorithm has been tested on several car plates and provides very satisfactory results.

  6. Nanomechanical recognition of prognostic biomarker suPAR with DVD-ROM optical technology

    Science.gov (United States)

    Bache, Michael; Bosco, Filippo G.; Brøgger, Anna L.; Frøhling, Kasper B.; Sonne Alstrøm, Tommy; Hwu, En-Te; Chen, Ching-Hsiu; Eugen-Olsen, Jesper; Hwang, Ing-Shouh; Boisen, Anja

    2013-11-01

    In this work the use of a high-throughput nanomechanical detection system based on a DVD-ROM optical drive and cantilever sensors is presented for the detection of urokinase plasminogen activator receptor inflammatory biomarker (uPAR). Several large scale studies have linked elevated levels of soluble uPAR (suPAR) to infectious diseases, such as HIV, and certain types of cancer. Using hundreds of cantilevers and a DVD-based platform, cantilever deflection response from antibody-antigen recognition is investigated as a function of suPAR concentration. The goal is to provide a cheap and portable detection platform which can carry valuable prognostic information. In order to optimize the cantilever response the antibody immobilization and unspecific binding are initially characterized using quartz crystal microbalance technology. Also, the choice of antibody is explored in order to generate the largest surface stress on the cantilevers, thus increasing the signal. Using optimized experimental conditions the lowest detectable suPAR concentration is currently around 5 nM. The results reveal promising research strategies for the implementation of specific biochemical assays in a portable and high-throughput microsensor-based detection platform.

  7. A new technique of recognition for coded targets in optical 3D measurement

    Science.gov (United States)

    Guo, Changye; Cheng, Xiaosheng; Cui, Haihua; Dai, Ning; Weng, Jinping

    2014-11-01

    A new technique for coded targets recognition in optical 3D-measurement application is proposed in this paper. Traditionally, point cloud registration is based on homologous features, such as the curvature, which is time-consuming and not reliable. For this, we paste some coded targets onto the surface of the object to be measured to improve the optimum target location and accurate correspondence among multi-source images. Circular coded targets are used, and an algorithm to automatically detecting them is proposed. This algorithm extracts targets with intensive bimodal histogram features from complex background, and filters noise according to their size, shape and intensity. In addition, the coded targets' identification is conducted out by their ring codes. We affine them around the circle inversely, set foreground and background respectively as 1 and 0 to constitute a binary number, and finally shift one bit every time to calculate a decimal one of the binary number to determine a minimum decimal number as its code. In this 3Dmeasurement application, we build a mutual relationship between different viewpoints containing three or more coded targets with different codes. Experiments show that it is of efficiency to obtain global surface data of an object to be measured and is robust to the projection angles and noise.

  8. Selective growth of silica nanowires using an Au catalyst for optical recognition of interleukin-10

    Science.gov (United States)

    Sekhar, Praveen K.; Ramgir, Niranjan S.; Joshi, Rakesh K.; Bhansali, Shekhar

    2008-06-01

    The vapor-liquid-solid (VLS) growth procedure has been extended for the selective growth of silica nanowires on SiO2 layer by using Au as a catalyst. The nanowires were grown in an open tube furnace at 1100 °C for 60 min using Ar as a carrier gas. The average diameter of these bottom-up nucleated wires was found to be 200 nm. Transmission electron microscopy analysis indicates the amorphous nature of these nanoscale wires and suggests an Si-silica heterostructure. The localized silica nanowires have been used as an immunoassay template in the detection of interleukin-10 which is a lung cancer biomarker. Such a nanostructured platform offered a tenfold enhancement in the optical response, aiding the recognition of IL-10 in comparison to a bare silica substrate. The role of nanowires in the immunoassay was verified through the quenching behavior in the photoluminescence (PL) spectra. Two orders of reduction in PL intensity have been observed after completion of the immunoassay with significant quenching after executing every step of the protocol. The potential of this site-specific growth of silica nanowires on SiO2 as a multi-modal biosensing platform has been discussed.

  9. Selective growth of silica nanowires using an Au catalyst for optical recognition of interleukin-10

    Energy Technology Data Exchange (ETDEWEB)

    Sekhar, Praveen K; Ramgir, Niranjan S; Joshi, Rakesh K; Bhansali, Shekhar [Bio-MEMS and Microfabrication Laboratory, Department of Electrical Engineering, University of South Florida, 4202 E Fowler Avenue, ENB 118, Tampa, FL 33620 (United States)], E-mail: bhansali@eng.usf.edu

    2008-06-18

    The vapor-liquid-solid (VLS) growth procedure has been extended for the selective growth of silica nanowires on SiO{sub 2} layer by using Au as a catalyst. The nanowires were grown in an open tube furnace at 1100 deg. C for 60 min using Ar as a carrier gas. The average diameter of these bottom-up nucleated wires was found to be 200 nm. Transmission electron microscopy analysis indicates the amorphous nature of these nanoscale wires and suggests an Si-silica heterostructure. The localized silica nanowires have been used as an immunoassay template in the detection of interleukin-10 which is a lung cancer biomarker. Such a nanostructured platform offered a tenfold enhancement in the optical response, aiding the recognition of IL-10 in comparison to a bare silica substrate. The role of nanowires in the immunoassay was verified through the quenching behavior in the photoluminescence (PL) spectra. Two orders of reduction in PL intensity have been observed after completion of the immunoassay with significant quenching after executing every step of the protocol. The potential of this site-specific growth of silica nanowires on SiO{sub 2} as a multi-modal biosensing platform has been discussed.

  10. Application of Convolutional Neural Network in Printed Code Characters Recognition%卷积神经网络在喷码字符识别中的应用

    Institute of Scientific and Technical Information of China (English)

    南阳; 白瑞林; 李新

    2015-01-01

    为实现易拉罐灌装过程中喷码字符实时检测,提出了一种基于卷积神经网络的实时检测方法。该方法首先对采集的图像进行直方图均衡化和OSTU处理,然后对图像进行形态学膨胀操作,通过连通域面积法提取出喷码字符区域并进行旋转矫正,再采用投影法将字符区域分割为单个字符,在离线状态下采用卷积神经网络对字符进行训练,从而在在线检测时进行识别。实验表明,该方法检测一帧图像平均时间为46 ms,准确率达98.97%,实时性和准确性较高,可以满足工业易拉罐喷码字符在线实时检测要求。%In order to achieve the real-time detection of Coding characters in the process of filling cans, a real-time detection method based on convolutional neural network is proposed. This method initially adopts the histogram equalization and OSTU to deal with the images and then operates the images by the morphological inflation method. Besides, the region of the printed code characters is extracted by the area method of connected domain and then rotates and corrects this region. By using the projection method, the region is divided into single characters which will be trained by the convolutional neural network under the offline state. All above procedures are done in order to recognize the characters while doing the online detection. Experiments show that the average time of every detected image is 46 ms and its accuracy achieves 98.97%which show high instantaneity and accuracy. Thus, it can meet the demand of the real-time detection of industrial cans characters.

  11. The optical properties of a-C:H films between 1.5 and 10 eV and the effect of thermal annealing on the film character

    Science.gov (United States)

    Logothetidis, S.; Petalas, J.; Ves, S.

    1996-01-01

    The optical properties of amorphous hydrogenated carbon films prepared with various techniques are studied with conventional and synchrotron-radiation spectroscopic ellipsometry (SE) and the pseudodielectric function of diamondlike and graphitelike films is presented in the energy region 1.5-10 eV. Characteristic features of the measured and the calculated electron-energy-loss (EEL) function are found to serve as useful criteria for the classification of such materials. The results and information obtained by SE are compared to those obtained by EEL and Raman spectroscopy techniques, which are the most widely used for this purpose. Thermal annealing experiments up to 675 °C with in situ monitoring of the reveal the undergoing structural changes in the material character from diamondlike into graphitelike during the annealing. The major modifications which turn the material into sp2-like are found to take place around and above 550 °C. The fundamental gap along with other optical parameters of the materials are compared to those of diamond and graphite and their shift with temperature is discussed and used to illustrate further the prevalence of the graphitic character during and after the annealing. Finally, the optimum growth parameters for the production of diamondlike material are discussed in the case of the glow-discharge and ion-beam deposited films.

  12. High-accuracy and robust face recognition system based on optical parallel correlator using a temporal image sequence

    Science.gov (United States)

    Watanabe, Eriko; Ishikawa, Mami; Ohta, Maiko; Kodate, Kashiko

    2005-09-01

    Face recognition is used in a wide range of security systems, such as monitoring credit card use, searching for individuals with street cameras via Internet and maintaining immigration control. There are still many technical subjects under study. For instance, the number of images that can be stored is limited under the current system, and the rate of recognition must be improved to account for photo shots taken at different angles under various conditions. We implemented a fully automatic Fast Face Recognition Optical Correlator (FARCO) system by using a 1000 frame/s optical parallel correlator designed and assembled by us. Operational speed for the 1: N (i.e. matching a pair of images among N, where N refers to the number of images in the database) identification experiment (4000 face images) amounts to less than 1.5 seconds, including the pre/post processing. From trial 1: N identification experiments using FARCO, we acquired low error rates of 2.6% False Reject Rate and 1.3% False Accept Rate. By making the most of the high-speed data-processing capability of this system, much more robustness can be achieved for various recognition conditions when large-category data are registered for a single person. We propose a face recognition algorithm for the FARCO while employing a temporal image sequence of moving images. Applying this algorithm to a natural posture, a two times higher recognition rate scored compared with our conventional system. The system has high potential for future use in a variety of purposes such as search for criminal suspects by use of street and airport video cameras, registration of babies at hospitals or handling of an immeasurable number of images in a database.

  13. Loose, Falling Characters and Sentences: The Persistence of the OCR Problem in Digital Repository E-Books

    Science.gov (United States)

    Kichuk, Diana

    2015-01-01

    The electronic conversion of scanned image files to readable text using optical character recognition (OCR) software and the subsequent migration of raw OCR text to e-book text file formats are key remediation or media conversion technologies used in digital repository e-book production. Despite real progress, the OCR problem of reliability and…

  14. Loose, Falling Characters and Sentences: The Persistence of the OCR Problem in Digital Repository E-Books

    Science.gov (United States)

    Kichuk, Diana

    2015-01-01

    The electronic conversion of scanned image files to readable text using optical character recognition (OCR) software and the subsequent migration of raw OCR text to e-book text file formats are key remediation or media conversion technologies used in digital repository e-book production. Despite real progress, the OCR problem of reliability and…

  15. Recognition of Text Image Using Multilayer Perceptron

    OpenAIRE

    Vijendra, Singh; Vasudeva, Nisha; Parashar, Hem Jyotsana

    2016-01-01

    The biggest challenge in the field of image processing is to recognize documents both in printed and handwritten format. Optical Character Recognition OCR is a type of document image analysis where scanned digital image that contains either machine printed or handwritten script input into an OCR software engine and translating it into an editable machine readable digital text format. A Neural network is designed to model the way in which the brain performs a particular task or function of int...

  16. Analysis on the clinical characters of optic neuritis caused by antituberculosis drugs%抗结核药物性视神经炎的临床分析

    Institute of Scientific and Technical Information of China (English)

    简奕娈; 古卓云; 魏琳; 张言斌

    2014-01-01

    目的:总结抗结核药物所致的视神经炎临床特点,探讨防治对策。  方法:回顾性分析广州市胸科医院2003-01/2013-01门诊和病房患者在抗结核治疗过程中出现药物性视神经炎的临床特点。  结果:抗结核药物治疗引起的药物性视神经炎不多见(17/60000),以球后视神经炎多见,引起视神经炎的抗结核药物主要是乙胺丁醇,其次是异烟肼、链霉素。明确诊断后及时停用与视神经炎相关的结核药,并根据病情给予补充维生素,扩张血管,激素等治疗,患者的视力都有不同程度的提高。  结论:在使用抗结核药期间要注意患者视力变化情况出现突发视力下降应作眼科检查,并及时给予干预,防止失明的严重后果。%To summarize the clinical characters of optic neuritis caused by antituberculosis drugs, and to discuss the prevention countermeasures. ● METHODS: The clinical characters of optic neuritis caused by antituberculosis drugs among those outpatients and ward patients from January 2003 to January 2013 were reviewed and analyzed. ● RESULTS: Optic neuritis caused by antituberculosis drugs was rare ( 17 / 60000 ), while retrobulbar neuritis was common. The drugs inducing optical neuritis were mainly ethambutol, followed by isoniazid and streptomycin. The vision of patients would have different degrees of improvement via the following treatment after specific diagnosis, i. e. , timely stopping the tuberculosis medicine associated with optic neuritis, and taking vitamin supplements, dilating blood vessels and applying hormone therapy according to the illness. ●CONCLUSlON: We should pay attention to the change of the vision of patients during the usage of antituberculosis drugs. ln the case of sudden eyesight deterioration, ophthalmology examination and timely treatment are advised preventing blindness.

  17. Believable Characters

    Science.gov (United States)

    El-Nasr, Magy Seif; Bishko, Leslie; Zammitto, Veronica; Nixon, Michael; Vasiliakos, Athanasios V.; Wei, Huaxin

    The interactive entertainment industry is one of the fastest growing industries in the world. In 1996, the U.S. entertainment software industry reported 2.6 billion in sales revenue, this figure has more than tripled in 2007 yielding 9.5 billion in revenues [1]. In addition, gamers, the target market for interactive entertainment products, are now reaching beyond the traditional 8-34 year old male to include women, Hispanics, and African Americans [2]. This trend has been observed in several markets, including Japan, China, Korea, and India, who has just published their first international AAA title (defined as high quality games with high budget), a 3D third person action game: Ghajini - The Game [3]. The topic of believable characters is becoming a central issue when designing and developing games for today's game industry. While narrative and character were considered secondary to game mechanics, games are currently evolving to integrate characters, narrative, and drama as part of their design. One can see this pattern through the emergence of games like Assassin's Creed (published by Ubisoft 2008), Hotel Dusk (published by Nintendo 2007), and Prince of Persia series (published by Ubisoft), which emphasized character and narrative as part of their design.

  18. An Embedded Application for Degraded Text Recognition

    Directory of Open Access Journals (Sweden)

    Thillou Céline

    2005-01-01

    Full Text Available This paper describes a mobile device which tries to give the blind or visually impaired access to text information. Three key technologies are required for this system: text detection, optical character recognition, and speech synthesis. Blind users and the mobile environment imply two strong constraints. First, pictures will be taken without control on camera settings and a priori information on text (font or size and background. The second issue is to link several techniques together with an optimal compromise between computational constraints and recognition efficiency. We will present the overall description of the system from text detection to OCR error correction.

  19. 深度学习在手写汉字识别中的应用综述%Applications of Deep Learning for Handwritten Chinese Character Recognition:A Review

    Institute of Scientific and Technical Information of China (English)

    金连文; 钟卓耀; 杨钊; 杨维信; 谢泽澄; 孙俊

    2016-01-01

    手写汉字识别(Handwritten Chinese character recognition, HCCR)是模式识别的一个重要研究领域,最近几十年来得到了广泛的研究与关注,随着深度学习新技术的出现,近年来基于深度学习的手写汉字识别在方法和性能上得到了突破性的进展。本文综述了深度学习在手写汉字识别领域的研究进展及具体应用。首先介绍了手写汉字识别的研究背景与现状。其次简要概述了深度学习的几种典型结构模型并介绍了一些主流的开源工具,在此基础上详细综述了基于深度学习的联机和脱机手写汉字识别的方法,阐述了相关方法的原理、技术细节、性能指标等现状情况,最后进行了分析与总结,指出了手写汉字识别领域仍需要解决的问题及未来的研究方向。%Handwritten Chinese character recognition (HCCR) is an important research filed of pattern recognition, which has attracted extensive studies during the past decades. With the emergence of deep learning, new breakthrough progresses of HCCR have been obtained in recent years. In this paper, we review the applications of deep learning models in the field of HCCR. First, the research background and current state-of-the-art HCCR technologies are introduced. Then, we provide a brief overview of several typical deep learning models, and introduce some widely used open source tools for deep learning. The approaches of online HCCR and offline HCCR based on deep learning are surveyed, with the summaries of the related methods, technical details, and performance analysis. Finally, further research directions are discussed.

  20. Robust Optical Recognition of Cursive Pashto Script Using Scale, Rotation and Location Invariant Approach

    National Research Council Canada - National Science Library

    Ahmad, Riaz; Naz, Saeeda; Afzal, Muhammad Zeshan; Amin, Sayed Hassan; Breuel, Thomas

    2015-01-01

    The presence of a large number of unique shapes called ligatures in cursive languages, along with variations due to scaling, orientation and location provides one of the most challenging pattern recognition problems...

  1. Robust Optical Recognition of Cursive Pashto Script Using Scale, Rotation and Location Invariant Approach: e0133648

    National Research Council Canada - National Science Library

    Riaz Ahmad; Saeeda Naz; Muhammad Zeshan Afzal; Sayed Hassan Amin; Thomas Breuel

    2015-01-01

      The presence of a large number of unique shapes called ligatures in cursive languages, along with variations due to scaling, orientation and location provides one of the most challenging pattern recognition problems...

  2. Logarithmic r-θ mapping for hybrid optical neural network filter for multiple objects recognition within cluttered scenes

    Science.gov (United States)

    Kypraios, Ioannis; Young, Rupert C. D.; Chatwin, Chris R.; Birch, Phil M.

    2009-04-01

    θThe window unit in the design of the complex logarithmic r-θ mapping for hybrid optical neural network filter can allow multiple objects of the same class to be detected within the input image. Additionally, the architecture of the neural network unit of the complex logarithmic r-θ mapping for hybrid optical neural network filter becomes attractive for accommodating the recognition of multiple objects of different classes within the input image by modifying the output layer of the unit. We test the overall filter for multiple objects of the same and of different classes' recognition within cluttered input images and video sequences of cluttered scenes. Logarithmic r-θ mapping for hybrid optical neural network filter is shown to exhibit with a single pass over the input data simultaneously in-plane rotation, out-of-plane rotation, scale, log r-θ map translation and shift invariance, and good clutter tolerance by recognizing correctly the different objects within the cluttered scenes. We record in our results additional extracted information from the cluttered scenes about the objects' relative position, scale and in-plane rotation.

  3. Tactile Recognition of Chinese Character and Two-finger Pattern%汉字触觉辨认与触觉双指模式

    Institute of Scientific and Technical Information of China (English)

    钱秀莹; 朱华军

    2003-01-01

    We tried to find the tactile identifying differences between Roman alphabet letter and Chinese character.Ten native Chinese speakers and ten native English speakers participated the visual-tactile matching experiment as subjects to see whether Chinese Character could be identified tactually or not.The result that showed no difference between two group of subjects inspired us to be one of forthgoers to study the tactile identifying of two tactile finger pattern,and further more the result supported the point that there is very similar interference effect associated with processes of identify single finger pattern or two finger pattern.%大量的以往研究涉及到字词识别,其中又有相当一部分是对字词或字母的触觉辨认研究,但未见汉字模式的触觉辨认研究.为了探讨汉字模式与英文字母或词模式触觉辨认的异同,我们先做简单汉字的视触匹配实验以确定此类实验是否可行.把10个高频且笔画少的汉字在6×24的触觉振动仪上转换成振动的触觉模式,由于汉字比以往触觉模式辨认实验中所用的单指振动模式要复杂,所以我们不得不把汉字转换成双指模式,即用了两片振动显示仪来呈现一个模式,被试用双指接触振动片.汉语母语被试与从没学过汉字的英语母语被试各10名对这些汉字触觉模式作了触觉与视觉模式匹配实验,结果表明两类被试的匹配成绩都很低而且无显著差异,结果可能是由于双指模式所致,从而不能完全说明汉字模式太难不适合触觉辨认,于是我们用单指模式的通常结构构建双指模式,使单双指模式的复杂度差异只表现在量上,检验了单双指模式的辨认效果,结果表明双指模式辨认成绩虽比单指辨认差但辨认中的认知特征如干扰中的反应竞争与知觉竞争效应相同.

  4. Vehicle License Plate Character Segmentation

    Institute of Scientific and Technical Information of China (English)

    Mei-Sen Pan; Jun-Biao Yan; Zheng-Hong Xiao

    2008-01-01

    Vehicle license plate (VLP) character segmentation is an important part of the vehicle license plate recognition system (VLPRS). This paper proposes a least square method (LSM) to treat horizontal tilt and vertical tilt in VLP images. Auxiliary lines are added into the image (or the tilt-corrected image) to make the separated parts of each Chinese character to be an interconnected region. The noise regions will be eliminated after two fusing images are merged according to the minimum principle of gray values.Then, the characters are segmented by projection method (PM) and the final character images are obtained. The experimental results show that this method features fast processing and good performance in segmentation.

  5. Automatic detection and recognition of multiple macular lesions in retinal optical coherence tomography images with multi-instance multilabel learning

    Science.gov (United States)

    Fang, Leyuan; Yang, Liumao; Li, Shutao; Rabbani, Hossein; Liu, Zhimin; Peng, Qinghua; Chen, Xiangdong

    2017-06-01

    Detection and recognition of macular lesions in optical coherence tomography (OCT) are very important for retinal diseases diagnosis and treatment. As one kind of retinal disease (e.g., diabetic retinopathy) may contain multiple lesions (e.g., edema, exudates, and microaneurysms) and eye patients may suffer from multiple retinal diseases, multiple lesions often coexist within one retinal image. Therefore, one single-lesion-based detector may not support the diagnosis of clinical eye diseases. To address this issue, we propose a multi-instance multilabel-based lesions recognition (MIML-LR) method for the simultaneous detection and recognition of multiple lesions. The proposed MIML-LR method consists of the following steps: (1) segment the regions of interest (ROIs) for different lesions, (2) compute descriptive instances (features) for each lesion region, (3) construct multilabel detectors, and (4) recognize each ROI with the detectors. The proposed MIML-LR method was tested on 823 clinically labeled OCT images with normal macular and macular with three common lesions: epiretinal membrane, edema, and drusen. For each input OCT image, our MIML-LR method can automatically identify the number of lesions and assign the class labels, achieving the average accuracy of 88.72% for the cases with multiple lesions, which better assists macular disease diagnosis and treatment.

  6. Role of Familiarity of Semantic Radicals in the Recognition of Lowly Familiar Chinese Characters%义符熟悉性对低频形声字词汇通达的影响

    Institute of Scientific and Technical Information of China (English)

    陈新葵; 张积家

    2012-01-01

    Chinese characters are logograms, with semantic radicals playing the dominating role in conveying meaning through form. Though fruitful results have been achieved in semantic radical's studies, providing evidence to support that semantic radical embodies the pictographic, ideographic and grammar function. The tasks applied in those studies are mostly outline, much less inline. The latter method mainly regards frequency as a balance-matching factor, while the matching method is likely to hide the difference in processing characters with different frequencies; this is probably one important reason why no concordant conclusion has been made in current semantic radical's studies. This study, referring to the Chen Xinkui and Zhang Jijias' research on the influence of the familiarity of semantic radicals on the recognition of high frequency Chinese characters, and applying the same research paradigm, I.e., by matching components of high frequency words and low frequency words like word frequency, number of strokes, details, contextual requisitions, probed into the impact of low frequency phonograms as initiate words on target words under three different SOA conditions, thus analyze systematically and thoroughly the impact of familiarity of semantic radicals on the understanding of phonograms. The results showed that when SOA = 43ms, the target latencies following R+S-primes were slower than the R - S - controls under the highly familiar semantic radical condition; however, this was not the case under the less familiar condition. When SOA = 72ms, the target latencies following R+S- primes were slowed relative to R - S - controls under both highly familiar and less familiar semantic radical conditions. Further, when SOA= 243ms, facilitation effects of R-S+ and inhibition effects of R+S- Primes were observed under both highly and lowly familiar semantic radicals conditions, with a inhibition effects found in the highly familiar one. The results indicated a dynamic

  7. Quantum-Limited Image Recognition

    Science.gov (United States)

    1989-12-01

    J. S. Bomba ,’Alpha-numeric character recognition using local operations,’ Fall Joint Comput. Conf., 218-224 (1959). 53. D. Barnea and H. Silverman...for Chapter 6 1. J. S. Bomba ,’Alpha-numeric character recognition using local operations,’ Fall Joint Comput. Conf., 218-224 (1959). 2. D. Bamea and H

  8. Robust Optical Recognition of Cursive Pashto Script Using Scale, Rotation and Location Invariant Approach.

    Science.gov (United States)

    Ahmad, Riaz; Naz, Saeeda; Afzal, Muhammad Zeshan; Amin, Sayed Hassan; Breuel, Thomas

    2015-01-01

    The presence of a large number of unique shapes called ligatures in cursive languages, along with variations due to scaling, orientation and location provides one of the most challenging pattern recognition problems. Recognition of the large number of ligatures is often a complicated task in oriental languages such as Pashto, Urdu, Persian and Arabic. Research on cursive script recognition often ignores the fact that scaling, orientation, location and font variations are common in printed cursive text. Therefore, these variations are not included in image databases and in experimental evaluations. This research uncovers challenges faced by Arabic cursive script recognition in a holistic framework by considering Pashto as a test case, because Pashto language has larger alphabet set than Arabic, Persian and Urdu. A database containing 8000 images of 1000 unique ligatures having scaling, orientation and location variations is introduced. In this article, a feature space based on scale invariant feature transform (SIFT) along with a segmentation framework has been proposed for overcoming the above mentioned challenges. The experimental results show a significantly improved performance of proposed scheme over traditional feature extraction techniques such as principal component analysis (PCA).

  9. Robust Optical Recognition of Cursive Pashto Script Using Scale, Rotation and Location Invariant Approach.

    Directory of Open Access Journals (Sweden)

    Riaz Ahmad

    Full Text Available The presence of a large number of unique shapes called ligatures in cursive languages, along with variations due to scaling, orientation and location provides one of the most challenging pattern recognition problems. Recognition of the large number of ligatures is often a complicated task in oriental languages such as Pashto, Urdu, Persian and Arabic. Research on cursive script recognition often ignores the fact that scaling, orientation, location and font variations are common in printed cursive text. Therefore, these variations are not included in image databases and in experimental evaluations. This research uncovers challenges faced by Arabic cursive script recognition in a holistic framework by considering Pashto as a test case, because Pashto language has larger alphabet set than Arabic, Persian and Urdu. A database containing 8000 images of 1000 unique ligatures having scaling, orientation and location variations is introduced. In this article, a feature space based on scale invariant feature transform (SIFT along with a segmentation framework has been proposed for overcoming the above mentioned challenges. The experimental results show a significantly improved performance of proposed scheme over traditional feature extraction techniques such as principal component analysis (PCA.

  10. An Efficient Hidden Markov Model for Offline Handwritten Numeral Recognition

    CERN Document Server

    Saritha, B S

    2010-01-01

    Traditionally, the performance of ocr algorithms and systems is based on the recognition of isolated characters. When a system classifies an individual character, its output is typically a character label or a reject marker that corresponds to an unrecognized character. By comparing output labels with the correct labels, the number of correct recognition, substitution errors misrecognized characters, and rejects unrecognized characters are determined. Nowadays, although recognition of printed isolated characters is performed with high accuracy, recognition of handwritten characters still remains an open problem in the research arena. The ability to identify machine printed characters in an automated or a semi automated manner has obvious applications in numerous fields. Since creating an algorithm with a one hundred percent correct recognition rate is quite probably impossible in our world of noise and different font styles, it is important to design character recognition algorithms with these failures in min...

  11. Multiple degree of freedom object recognition using optical relational graph decision nets

    Science.gov (United States)

    Casasent, David P.; Lee, Andrew J.

    1988-01-01

    Multiple-degree-of-freedom object recognition concerns objects with no stable rest position with all scale, rotation, and aspect distortions possible. It is assumed that the objects are in a fairly benign background, so that feature extractors are usable. In-plane distortion invariance is provided by use of a polar-log coordinate transform feature space, and out-of-plane distortion invariance is provided by linear discriminant function design. Relational graph decision nets are considered for multiple-degree-of-freedom pattern recognition. The design of Fisher (1936) linear discriminant functions and synthetic discriminant function for use at the nodes of binary and multidecision nets is discussed. Case studies are detailed for two-class and multiclass problems. Simulation results demonstrate the robustness of the processors to quantization of the filter coefficients and to noise.

  12. Recognition of Devoiced Vowels Using Optical Microphone Made of Multipled POF-Type Moisture Sensors

    Science.gov (United States)

    Morisawa, Masayuki; Natori, Yoichi; Taki, Tomohito; Muto, Shinzo

    A novel optical fiber microphone system for recognizing devoiced vowels has been studied. This system consists of the optical detection of moisture pattern formed by devoiced breath and its recognization process using a modified DP-matching. To detect moisture pattern of devoiced vowels, five plastic optical fiber moisture sensors with fast response were developed and used. Using this system, high discernment rate over 93% was obtained for the devoiced vowels. This system will be used for verbally handicapped people to create sounds with a small effort in the near future.

  13. A word level segmentation for off-line Arabic characters

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    Segmentation of cursive text has been one of the major problems in Arabic writing. The problem is the shape of the letter which is context sensitive, depending on it' s location within a word. Many text recognition systems recognize text imagery at the character level and assemble words from the recognized characters.Unfortunately this approach does not work with Arabic text. In this paper we describe a new approach to segment Arabic text imagery at a word level, without analyzing individual characters. This approach avoids the problem of individual characters segmentation, and can overcome local errors in character recognition.

  14. Interest of correlation-based automatic target recognition in underwater optical images: theoretical justification and first results

    Science.gov (United States)

    Leonard, I.; Arnold-Bos, A.; Alfalou, A.

    2010-04-01

    In this paper, we explore the use of optical correlation-based recognition to identify and position underwater man-made objects (e.g. mines). Correlation techniques can be defined as a simple comparison between an observed image (image to recognize) and a reference image; they can be achieved extremely fast. The result of this comparison is a more or less intense correlation peak, depending on the resemblance degree between the observed image and a reference image coming from a database. However, to perform a good correlation decision, we should compare our observed image with a huge database of references, covering all the appearances of objects we search. Introducing all the appearances of objects can influence speed and/or recognition quality. To overcome this limitation, we propose to use composite filter techniques, which allow the fusion of several references and drastically reduce the number of needed comparisons to identify observed images. These recent techniques have not yet been exploited in the underwater context. In addition, they allow for integrating some preprocessing directly in the correlation filter manufacturing step to enhance the visibility of objects. Applying all the preprocessing in one step reduces the processing by avoiding unnecessary Fourier transforms and their inverse operation. We want to obtain filters that are independent from all noises and contrast problems found in underwater videos. To achieve this and to create a database containing all scales and viewpoints, we use as references 3D computer-generated images.

  15. All Optical Three Dimensional Spatio-Temporal Correlator for Automatic Event Recognition Using Multiphoton Atomic System

    CERN Document Server

    Monjur, Mehjabin S; Shahriar, Selim M

    2015-01-01

    In this paper, we model and show the simulation results of a three-dimensional spatio-temporal correlator (STC) that combines the technique of holographic correlation and photon echo based temporal pattern recognition. The STC is shift invariant in space and time. It can be used to recognize rapidly an event (e.g., a short video clip) that may be present in a large video file, and determine the temporal location of the event. It can also determine multiple matches automatically if the event occurs more than once. We show how to realize the STC using Raman transitions in Rb atomic vapor.

  16. Character Recognition Using Novel Optoelectronic Neural Network

    Science.gov (United States)

    1993-04-01

    17 2.3.7. Learning rule ................................................................... 18 3. ADALINE ... ADALINE neuron and linear separability which provides a justification for multilayer networks. The MADALINE (many ADALINE ) multi layer network is also...element used In many neural networks (Figure 3.1). The ADALINE functions as an adaptive threshold logic element. In digital Implementation, an input

  17. LabeI Character Recognition Based on Image Composition of DoubIe Light Sources%基于双光源图像合成法的标牌字符识别方法研究

    Institute of Scientific and Technical Information of China (English)

    林笃盛; 吕海堂; 洪涛; 周明华

    2014-01-01

    在电能表标牌 OCR 的识别过程中,标牌上的透明薄膜经常出现皱褶,使得待识别字符极易受到反射光遮挡,从而增加了 OCR 的识别难度和识别错误率。提出一种位置对称的双光源图像合成法,用该方法检测了多个贴有皱褶薄膜层的电能表标牌,经实例验证,相较于单光源的识别错误率大幅度降低,这有效解决了电能表标牌 OCR 中薄膜反光干扰问题。%The Watt-hour meter sign of transparent fiIm often appears corrugated surface during the OCR process,which makes waiting characters are screened by refIected Iight easiIy,increases the difficuIty of OCR recognition and discriminating error rate.This paper presents a symmetricaI site of doubIe Iight sources image composition method,which is used to identify the number of watt-hour meter signs with corrugated surface.It has been verified by exampIes that compared with singIe Iight source reduced greatIy the discriminating error rate,and soIved effectiveIy the watt-hour meter sign OCR of refIective fiIm interference probIem.

  18. Nearest Neighbor Algorithm in Handwritten Character

    Directory of Open Access Journals (Sweden)

    P. R. Deshmukh

    2014-07-01

    Full Text Available The proposed system extracts the geometric features of the character Contour. The system gives a feature vector as its output. The feature vectors so generated from a training set is then used to train a pattern recognition engine based on Neural Networks so that the system can be benchmarked. There was an attempt made to develop a system that used the methods that humans use to perceive handwritten characters. Hence a system that recognizes handwritten characters using Pattern recognition was developed. Here the data generated by comparing two images was stored in excel format and then that data was called as an individual input for generation of Simulink diagram. Pattern recognition can be used to model human perception. The mathematics that Pattern recognition requires is extremely fundamental. Any algorithm developed using Pattern recognition would require relatively simple and not so lengthy calculations. Due to simplicity of calculations, they can be implemented on any hardware or software platform without worrying about the computing power. In this paper first part is about introduction to character Recognition. The second part deals with the short introduction to neural network implementation for image processing using MATLAB

  19. Linear methods for input scenes restoration from signals of optical-digital pattern recognition correlator

    Science.gov (United States)

    Starikov, Sergey N.; Konnik, Mikhail V.; Manykin, Edward A.; Rodin, Vladislav G.

    2009-04-01

    Linear methods of restoration of input scene's images in optical-digital correlators are described. Relatively low signal to noise ratio of a camera's photo sensor and extensional PSF's size are special features of considered optical-digital correlator. RAW-files of real correlation signals obtained by digital photo sensor were used for input scene's images restoration. It is shown that modified evolution method, which employs regularization by Tikhonov, is better among linear deconvolution methods. As a regularization term, an inverse signal to noise ratio as a function of spatial frequencies was used. For additional improvement of restoration's quality, noise analysis of boundary areas of the image to be reconstructed was performed. Experimental results on digital restoration of input scene's images are presented.

  20. Recognition of serous ovarian tumors in human samples by multimodal nonlinear optical microscopy

    Science.gov (United States)

    Adur, Javier; Pelegati, Vitor B.; Costa, Leverson F. L.; Pietro, Luciana; de Thomaz, Andre A.; Almeida, Diogo B.; Bottcher-Luiz, Fatima; Andrade, Liliana A. L. A.; Cesar, Carlos L.

    2011-09-01

    We used a multimodal nonlinear optics microscopy, specifically two-photon excited fluorescence (TPEF), second and third harmonic generation (SHG/THG) microscopies, to observe pathological conditions of ovarian tissues obtained from human samples. We show that strong TPEF + SHG + THG signals can be obtained in fixed samples stained with hematoxylin and eosin (H&E) stored for a very long time, and that H&E staining enhanced the THG signal. We then used the multimodal TPEF-SHG-THG microscopies in a stored file of H&E stained samples of human ovarian cancer to obtain complementary information about the epithelium/stromal interface, such as the transformation of epithelium surface (THG) and the overall fibrillary tissue architecture (SHG). This multicontrast nonlinear optics microscopy is able to not only differentiate between cancerous and healthy tissue, but can also distinguish between normal, benign, borderline, and malignant specimens according to their collagen disposition and compression levels within the extracellular matrix. The dimensions of the layers of epithelia can also be measured precisely and automatically. Our data demonstrate that optical techniques can detect pathological changes associated with ovarian cancer.

  1. Practical vision based degraded text recognition system

    Science.gov (United States)

    Mohammad, Khader; Agaian, Sos; Saleh, Hani

    2011-02-01

    Rapid growth and progress in the medical, industrial, security and technology fields means more and more consideration for the use of camera based optical character recognition (OCR) Applying OCR to scanned documents is quite mature, and there are many commercial and research products available on this topic. These products achieve acceptable recognition accuracy and reasonable processing times especially with trained software, and constrained text characteristics. Even though the application space for OCR is huge, it is quite challenging to design a single system that is capable of performing automatic OCR for text embedded in an image irrespective of the application. Challenges for OCR systems include; images are taken under natural real world conditions, Surface curvature, text orientation, font, size, lighting conditions, and noise. These and many other conditions make it extremely difficult to achieve reasonable character recognition. Performance for conventional OCR systems drops dramatically as the degradation level of the text image quality increases. In this paper, a new recognition method is proposed to recognize solid or dotted line degraded characters. The degraded text string is localized and segmented using a new algorithm. The new method was implemented and tested using a development framework system that is capable of performing OCR on camera captured images. The framework allows parameter tuning of the image-processing algorithm based on a training set of camera-captured text images. Novel methods were used for enhancement, text localization and the segmentation algorithm which enables building a custom system that is capable of performing automatic OCR which can be used for different applications. The developed framework system includes: new image enhancement, filtering, and segmentation techniques which enabled higher recognition accuracies, faster processing time, and lower energy consumption, compared with the best state of the art published

  2. Printed Persian Subword Recognition Using Wavelet Packet Descriptors

    Directory of Open Access Journals (Sweden)

    Samira Nasrollahi

    2013-01-01

    Full Text Available In this paper, we present a new approach to offline OCR (optical character recognition for printed Persian subwords using wavelet packet transform. The proposed algorithm is used to extract font invariant and size invariant features from 87804 subwords of 4 fonts and 3 sizes. The feature vectors are compressed using PCA. The obtained feature vectors yield a pictorial dictionary for which an entry is the mean of each group that consists of the same subword with 4 fonts in 3 sizes. The sets of these features are congregated by combining them with the dot features for the recognition of printed Persian subwords. To evaluate the feature extraction results, this algorithm was tested on a set of 2000 subwords in printed Persian text documents. An encouraging recognition rate of 97.9% is got at subword level recognition.

  3. Recognition without cued recall (RWCR) phenomenon in Chinese characters: Effects of restudying and testing%汉字的无线索回忆再认效应:重复学习和重复测验的作用

    Institute of Scientific and Technical Information of China (English)

    贾永萍; 周楚; 李林; 郭秀艳

    2016-01-01

    characters learning, and used RWCR to examine the effectiveness of testing and restudying in recognition. In Experiment 1, the final recognition test was taken immediately after the learning phase. A total of 60 college students were engaged in a 2 (Study Status: studied vs. nonstudied) × 2 (Study Strategy Type: testing vs. repeated study) mixed design experiment, to study different influences of testing and restudying on effectiveness of recollection and familiarity. In Experiment 2, 41 college students participated in a mixed design experiment. The procedure was identical to that of experiment 1, except that the final recognition test was taken one week after learning. The results showed that (1) when the final test was taken immediately after the study phase, both restudying and testing lead to better recollection performance than the studying-once encoding did, and there was an advantage of restudy encoding over test encoding. (2) Restudy encoding led to better familiarity performance relative to testing and study-once encoding, and there was no difference between test encoding and studying-once encoding. (3) When the final test was delayed for one week, there was no difference in the recollection performance after either restudy encoding or test encoding. (4) Familiarity performance in restudy encoding condition declined faster than that in the test encoding condition. (5) The semantics of Chinese could elicit the RWCR effect. The results demonstrated that the initial testing increased recollection relative to studying words once, whereas it did not affect familiarity. In addition, recognition tasks showed better familiarity on restudied words than on tested words, and test could enhance long-term retention of the tested material. Further, the semantics of word would also elicit the RWCR effect in logographically scripted language (i.e., Chinese).

  4. Automatic recognition of printed Oriya script

    Indian Academy of Sciences (India)

    B B Chaudhuri; U Pal; M Mitra

    2002-02-01

    This paper deals with an Optical Character Recognition (OCR) system for printed Oriya script. The development of OCR for this script is difficult because a large number of character shapes in the script have to be recognized. In the proposed system, the document image is first captured using a flat-bed scanner and then passed through different preprocessing modules like skew correction, line segmentation, zone detection, word and character segmentation etc. These modules have been developed by combining some conventional techniques with some newly proposed ones. Next, individual characters are recognized using a combination of stroke and run-number based features, along with features obtained from the concept of water overflow from a reservoir. The feature detection methods are simple and robust, and do not require preprocessing steps like thinning and pruning. A prototype of the system has been tested on a variety of printed Oriya material, and currently achieves 96.3% character level accuracy on average.

  5. Characters with personality!

    NARCIS (Netherlands)

    Bosch, K. van den; Brandenburgh, A.; Muller, T.J.; Heuvelink, A.

    2012-01-01

    Serious games offer an opportunity for learning communication skills by practicing conversations with one or more virtual characters, provided that the character(s) behave in accordance with their assigned properties and strate-gies. This paper presents an approach for developing virtual characters

  6. Generalized regression neural network trained preprocessing of frequency domain correlation filter for improved face recognition and its optical implementation

    Science.gov (United States)

    Banerjee, Pradipta K.; Datta, Asit K.

    2013-02-01

    The paper proposes an improved strategy for face recognition using correlation filter under varying lighting conditions and occlusion where spatial domain preprocessing is carried out by two convolution kernels. The first convolution kernel is a contour kernel for emphasizing high frequency components of face image and the other kernel is a smoothing kernel used for minimization of noise those may arise due to preprocessing. The convolution kernels are obtained by training a generalized regression neural network using enhanced face features. Face features are enhanced by conventional principal component analysis. The proposed method reduces the false acceptance rate and false rejection rate in comparison to other standard correlation filtering techniques. Moreover, the processing is fast when compared to the existing illumination normalization techniques. A scheme of hardware implementation of all optical correlation technique is also suggested based on single spatial light modulator in a beam folding architecture. Two benchmark databases YaleB and PIE are used for performance verification of the proposed scheme and the improved results are obtained for both illumination variations and occlusions in test face images.

  7. Amino acids recognition by water-soluble uncharged porphyrin tweezers: Spectroscopic evidences in high optical density solutions

    Energy Technology Data Exchange (ETDEWEB)

    Villari, Valentina, E-mail: villari@me.cnr.it [CNR-IPCF Istituto per i Processi Chimico-Fisici, V.le F. Stagno d' Alcontres 37, I-98158 Messina (Italy); Mineo, Placido, E-mail: gmineo@unict.it [CNR-IPCF Istituto per i Processi Chimico-Fisici, V.le F. Stagno d' Alcontres 37, I-98158 Messina (Italy); Dipartimento di Scienze Chimiche, Universita di Catania, Viale Andrea Doria 6, I-95125 Catania (Italy); Scamporrino, Emilio [Dipartimento di Scienze Chimiche, Universita di Catania, Viale Andrea Doria 6, I-95125 Catania (Italy); Micali, Norberto [CNR-IPCF Istituto per i Processi Chimico-Fisici, V.le F. Stagno d' Alcontres 37, I-98158 Messina (Italy)

    2012-06-19

    Highlights: Black-Right-Pointing-Pointer Molecular recognition properties of metal bis-porphyrins at high concentration. Black-Right-Pointing-Pointer The formation of the complex causes the disruption of the aggregates. Black-Right-Pointing-Pointer High sensitivity for the optical detection of low amount of amino acids. Black-Right-Pointing-Pointer Potential applications as a selective molecular sensor of amino acids. - Abstract: Small angle X-ray measurements on concentrated solutions of Cobalt-bis-porphyrins showed, at all the investigated concentration values, the presence of small aggregates which possess a sphere-like shape with a homogeneous electron density distribution. Such an aggregation, however, is proven not to affect the binding properties of the molecules with amino acids. Indeed, the Cobalt ion of the bis-porphyrins are available for coordinating the nitrogen atom of the amino acid to form a stable complex, as indicated by UV-vis and circular dichroism spectroscopy. The ability of these uncharged water-soluble bis-porphyrins to act as molecular sensors of amino acids in a wide concentration range takes great relevance in biosensing applications for which high concentration might be required.

  8. Offline Handwritten Devanagari Script Recognition

    Directory of Open Access Journals (Sweden)

    Ved Prakash Agnihotri

    2012-07-01

    Full Text Available Handwritten Devanagari script recognition system using neural network is presented in this paper. Diagonal based feature extraction is used for extracting features of the handwritten Devanagari script. After that these feature of each character image is converted into chromosome bit string of length 378. More than 1000 sample is used for training and testing purpose in this proposed work. It is attempted to use the power of genetic algorithm to recognize the character. In step-I preprocessing on the character image, then image suitable for feature extraction as here is used. Diagonal based feature extraction method to extract 54 features to each character. In the next step character recognize image in which extracted feature in converted into Chromosome bit string of size 378. In recognition step using fitness function in which find the Chromosome difference between unknown character and Chromosome which are store in data base.

  9. Target recognition by wavelet transform

    CERN Document Server

    Li Zheng Dong; He Wu Liang; Pei Chun Lan; Peng Wen; SongChen; Zheng Xiao Dong

    2002-01-01

    Wavelet transform has an important character of multi-resolution power, which presents pyramid structure, and this character coincides the way by which people distinguish object from coarse to fineness and from large to tiny. In addition to it, wavelet transform benefits to reducing image noise, simplifying calculation, and embodying target image characteristic point. A method of target recognition by wavelet transform is provided

  10. Optical correlation filters for large-class OCR applications

    Science.gov (United States)

    Casasent, David P.; Iyer, Anand K.; Gopalaswamy, Srinivasan

    1991-08-01

    The performance of two new optical correlation filters (G-MACE and MINACE) for large class (many fonts and true class words) OCR (optical character recognition) applications is considered. We consider filters that can recognize many key words in upper case (UC) and mixed case (MC) and various point sizes in the presence of OCR scanner sampling errors. New results are presented and guidelines for large class filters are advanced.

  11. On Multiple Typeface Arabic Script Recognition

    Directory of Open Access Journals (Sweden)

    Abdelmalek Zidouri

    2010-08-01

    Full Text Available In this study, we propose a new sub-word segmentation and recognition scheme, which is independent of font size and font type. D ifferent ways of recognition are attempted namely Neural N et, template matching and principal component analysis. Results show that the real problem in Arabic character recognition remains the challenging separation of sub-words into characters. The system is realized in a modularized way. The combination of the different modules forms the basis of a complete Arabic OCR system. A successful preprocessing stage is reported. Unlike Latin based languages, recognition of printed Arabic characters remains an open field of research.

  12. Actor/Character Dualism

    DEFF Research Database (Denmark)

    Riis, Johannes

    2012-01-01

    Our perception of agency may be inherently fallible, and this may explain not only our general awareness of actors when engaged in fictional characters but also the specific case of paradoxical characters...

  13. Hierarchical Approximate Matching for Retrieval of Chinese Historical Calligraphy Character

    Institute of Scientific and Technical Information of China (English)

    Xia-Fen Zhang; Yue-Ting Zhuang; Jiang-Qin Wu; Fei Wu

    2007-01-01

    As historical Chinese calligraphy works are being digitized, the problem of retrieval becomes a new challenge. But, currently no OCR technique can convert calligraphy character images into text, nor can the existing Handwriting Character Recognition approach does not work for it. This paper proposes a novel approach to efficiently retrieving Chinese calligraphy characters on the basis of similarity: calligraphy character image is represented by a collection of discriminative features, and high retrieval speed with reasonable effectiveness is achieved. First, calligraphy characters that have no possibility similar to the query are filtered out step by step by comparing the character complexity, stroke density and stroke protrusion. Then, similar calligraphy characters are retrieved and ranked according to their matching cost produced by approximate shape match. In order to speed up the retrieval, we employed high dimensional data structure-PK-tree. Finally, the efficiency of the algorithm is demonstrated by a preliminary experiment with 3012 calligraphy character images.

  14. On Chinese Character

    Institute of Scientific and Technical Information of China (English)

    杨文娟

    2016-01-01

    Just as the long history of our country, Chinese characters also have their long histories through thousands of years. There have been many great scientific works or documents studying on the origin of Chinese characters. From them, it can easily be found that each Chinese character has its own history. If we study on the history of a specific Chinese character, its motivation will be found.

  15. Back Propagation Neural Network Arabic Characters Classification Module Utilizing Microsoft Word

    Directory of Open Access Journals (Sweden)

    A. A. Hamza

    2008-01-01

    Full Text Available Problem statement: Arabic character recognition has been one of the last major languages to receive attention. This may be attributed to the inherent complexity of both printed and handwritten Arabic characters. The objectives of this study were to: (i summarize the main characteristics of Arabic language writing style. (ii suggest a neural network recognition circuit. Approach: A Neural network with back propagation training mechanism for classification was designed and trained to recognize any set of character combinations, sizes or fonts used in Microsoft word. Results: The proposed network recognition behaviours were compared with perceptron-like net that combines perceptron with ADALINE features. These circuits were tested for three character sets combinations; 28 basic Arabic characters plus 10 numerals set, 52 Latin characters and 10 numerals only. Conclusions: The method was robust and flexible and can be easily extended to any character set. The network exhibited recognition rates approaching 100% with reasonable noise tolerance.

  16. Handwritten Character Classification using the Hotspot Feature Extraction Technique

    NARCIS (Netherlands)

    Surinta, Olarik; Schomaker, Lambertus; Wiering, Marco

    2012-01-01

    Feature extraction techniques can be important in character recognition, because they can enhance the efficacy of recognition in comparison to featureless or pixel-based approaches. This study aims to investigate the novel feature extraction technique called the hotspot technique in order to use it

  17. Visual Recognition and Its Application to Robot Arm Control

    Directory of Open Access Journals (Sweden)

    Jih-Gau Juang

    2015-10-01

    Full Text Available This paper presents an application of optical word recognition and fuzzy control to a smartphone automatic test system. The system consists of a robot arm and two webcams. After the words from the control panel that represent commands are recognized by the robot system, the robot arm performs the corresponding actions to test the smartphone. One of the webcams is utilized to capture commands on the screen of the control panel, the other to recognize the words on the screen of the tested smartphone. The method of image processing is based on the Red-Green-Blue (RGB and Hue-Saturation-Luminance (HSL color spaces to reduce the influence of light. Fuzzy theory is used in the robot arm’s position control. The Optical Character Recognition (OCR technique is applied to the word recognition, and the recognition results are then checked by a dictionary process to increase the recognition accuracy. The camera which is used to recognize the tested smartphone also provides object coordinates to the fuzzy controller, then the robot arm moves to the desired positions and presses the desired buttons. The proposed control scheme allows the robot arm to perform different assigned test functions successfully.

  18. ADAPTIVE CHARACTER RECOGNIZER FOR A HAND­HELD DEVICE : IMPLEMENTATION AND EVALUATION SETUP

    NARCIS (Netherlands)

    Vuori, V.; Aksela, M.; Laaksonen, J.; Oja, E.; Kangas, J.

    2004-01-01

    In this work, we describe a character recognition system we have implemented for experimenting with self­supervised adaptation method. The Dynamic Time Warping algorithm is used for matching input characters to prototypes and recognition is carried out according to the k­nearest neighbor rule. The

  19. The positioning algorithm based on feature variance of billet character

    Science.gov (United States)

    Yi, Jiansong; Hong, Hanyu; Shi, Yu; Chen, Hongyang

    2015-12-01

    In the process of steel billets recognition on the production line, the key problem is how to determine the position of the billet from complex scenes. To solve this problem, this paper presents a positioning algorithm based on the feature variance of billet character. Using the largest intra-cluster variance recursive method based on multilevel filtering, the billet characters are segmented completely from the complex scenes. There are three rows of characters on each steel billet, we are able to determine whether the connected regions, which satisfy the condition of the feature variance, are on a straight line. Then we can accurately locate the steel billet. The experimental results demonstrated that the proposed method in this paper is competitive to other methods in positioning the characters and it also reduce the running time. The algorithm can provide a better basis for the character recognition.

  20. Formation of nanoscale spatially indirect excitons: Evolution of the type-II optical character of CdTe/CdSe heteronanocrystals

    NARCIS (Netherlands)

    de Mello Donega, C.

    2010-01-01

    In this work, the evolution of the optical properties of nanoscale spatially indirect excitons as a function of the size, shape, and composition of the heteronanostructure is investigated, using colloidal CdTe/CdSe heteronanocrystals (2.6 nm diameter CdTe core and increasing CdSe volume fraction) as

  1. About Chinese Characters

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    The character "力" li (strength) was originally written "(?)" The curving " (?) " indicates bulging muscles, while the "(?)" component represents skin. Despite its evolution over the centuries, "力" still symbolizes a strong arm.In combination with other characters "力" conveys the meaning "力量" liliang (strength), "力气"liqi (strength), "力求" liqiu (pursue) and "力争" lizheng (strive).

  2. Image simulation for automatic license plate recognition

    Science.gov (United States)

    Bala, Raja; Zhao, Yonghui; Burry, Aaron; Kozitsky, Vladimir; Fillion, Claude; Saunders, Craig; Rodríguez-Serrano, José

    2012-01-01

    Automatic license plate recognition (ALPR) is an important capability for traffic surveillance applications, including toll monitoring and detection of different types of traffic violations. ALPR is a multi-stage process comprising plate localization, character segmentation, optical character recognition (OCR), and identification of originating jurisdiction (i.e. state or province). Training of an ALPR system for a new jurisdiction typically involves gathering vast amounts of license plate images and associated ground truth data, followed by iterative tuning and optimization of the ALPR algorithms. The substantial time and effort required to train and optimize the ALPR system can result in excessive operational cost and overhead. In this paper we propose a framework to create an artificial set of license plate images for accelerated training and optimization of ALPR algorithms. The framework comprises two steps: the synthesis of license plate images according to the design and layout for a jurisdiction of interest; and the modeling of imaging transformations and distortions typically encountered in the image capture process. Distortion parameters are estimated by measurements of real plate images. The simulation methodology is successfully demonstrated for training of OCR.

  3. Knowing Chinese character grammar.

    Science.gov (United States)

    Myers, James

    2016-02-01

    Chinese character structure has often been described as representing a kind of grammar, but the notion of character grammar has hardly been explored. Patterns in character element reduplication are particularly grammar-like, displaying discrete combinatoriality, binarity, phonology-like final prominence, and potentially the need for symbolic rules (X→XX). To test knowledge of these patterns, Chinese readers were asked to judge the acceptability of fake characters varying both in grammaticality (obeying or violating reduplication constraints) and in lexicality (of the reduplicative configurations). While lexical knowledge was important (lexicality improved acceptability and grammatical configurations were accepted more quickly when also lexical), grammatical knowledge was important as well, with grammaticality improving acceptability equally for lexical and nonlexical configurations. Acceptability was also higher for more frequent reduplicative elements, suggesting that the reduplicative configurations were decomposed. Chinese characters present an as-yet untapped resource for exploring fundamental questions about the nature of the human capacity for grammar.

  4. Radical Sensitivity Is the Key to Understanding Chinese Character Acquisition in Children

    Science.gov (United States)

    Tong, Xiuhong; Tong, Xiuli; McBride, Catherine

    2017-01-01

    This study investigated Chinese children's development of sensitivity to positional (orthographic), phonological, and semantic cues of radicals in encoding novel Chinese characters. A newly designed picture-novel character mapping task, along with nonverbal reasoning ability, vocabulary, and Chinese character recognition were administered to 198…

  5. Good initialization model with constrained body structure for scene text recognition

    Science.gov (United States)

    Zhu, Anna; Wang, Guoyou; Dong, Yangbo

    2016-09-01

    Scene text recognition has gained significant attention in the computer vision community. Character detection and recognition are the promise of text recognition and affect the overall performance to a large extent. We proposed a good initialization model for scene character recognition from cropped text regions. We use constrained character's body structures with deformable part-based models to detect and recognize characters in various backgrounds. The character's body structures are achieved by an unsupervised discriminative clustering approach followed by a statistical model and a self-build minimum spanning tree model. Our method utilizes part appearance and location information, and combines character detection and recognition in cropped text region together. The evaluation results on the benchmark datasets demonstrate that our proposed scheme outperforms the state-of-the-art methods both on scene character recognition and word recognition aspects.

  6. 集装箱编码图像的识别%Container Image ID Recognition

    Institute of Scientific and Technical Information of China (English)

    朱秋煜; 韩锦成; 阚伟

    2000-01-01

    The paper studies a technique of container image ID recognition. In the image preprocessing phase, thresholdiong based on histogram and adaptive thresholding is used. In the character segmentation phase, a labeling method is used, which is based on connected region, location of character block, location of character line recovery of absent and fragmented characters. In the recognition phase, adaptive template match and multiple image results synthesis are used. A high recognition rate is obtained.

  7. 集装箱编码图像的识别%Container Image ID Recognition

    Institute of Scientific and Technical Information of China (English)

    朱秋煜; 韩锦成; 阚伟

    2001-01-01

    The paper studies a technique of container image ID recognition. In the image preprocessing phase, thresholdiong based on histogram and adaptive thresholding is used. In the character segmentation phase, a labeling method is used, which is based on connected region, location of character block, location of character line recovery of absent and fragmented characters. In the recognition phase, adaptive template match and multiple image results synthesis are used. A high recognition rate is obtained.

  8. CHR -- Character Handling Routines

    Science.gov (United States)

    Charles, A. C.; Rees, P. C. T.; Chipperfield, A. J.; Jenness, T.

    This document describes the Character Handling Routine library, CHR, and its use. The CHR library augments the limited character handling facilities provided by the Fortran 77 standard. It offers a range of character handling facilities: from formatting Fortran data types into text strings and the reverse, to higher level functions such as wild card matching, string sorting, paragraph reformatting and justification. The library may be used simply for building text strings for interactive applications or as a basis for more complex text processing applications.

  9. Madness in Shakespeare's Characters

    Directory of Open Access Journals (Sweden)

    Nuno Borja-Santos

    2014-10-01

    Full Text Available This paper begins with an introduction where the aims are explained: a psychopathological analysis of a Shakespearean character - Othello – followed by the discussion of the English dramatist’s importance in helping us understand madness in the emergent world of Renaissance. The main characteristics of Othello’s personality, which allowed the development of his jealousy delusion, are described. Finally, the conclusions underline the overlap of the symptoms developed by the character with the DSM-IV classification.

  10. 基于光流空间分布的步态识别方法%Gait recognition method based on spatial distribution of optical flow

    Institute of Scientific and Technical Information of China (English)

    杨阳; 郭继昌

    2013-01-01

    Concerning the disadvantages of the traditional gait recognition method based on optical flow,such as complex system and low recognition rate.This paper proposed an improved model-free method—the spatial distribution of the optical flow to descript and recognize moving target.First,it computed dense optical flow for each image in a sequence and derive scale-independent scalar features which characterized the spatial distribution of the flow.Then,it analyzed periodic structure of these sequences of scalars.The scalar sequences for an image sequence has the same fundamental period but differ in phase.The phase feature vectors could be used to recognize individuals.Lastly,for each sample,trained the average of feature vectors as cluster centers.Sequences were classified to the nearest class based on the nearest neighbor rule.The experiment results show that,in the CASIA gait database,90% recognition rate or higher can be reached.%针对传统基于光流法步态识别复杂、识别率不高的缺点,提出了一种非模型化的方法——光流空间分布来描述并识别运动目标.首先,计算每帧步态序列中的密度光流场,所得的与尺度无关的矩描述了光流的空间形状分布;然后,分析每一组矩的周期性结构特征,不同图像序列对应的矢量有基本相同的周期特征和不同的相位特征,利用相位特征区分不同个体步态之间的差异;最后,训练时计算各个样本特征矢量的平均值作为聚类中心,识别时计算待识别序列矢量和每个聚类中心的距离,采用最近邻法则,把序列归类到距离最近的类中.实验证明,该算法在CASIA步态数据库上最高能达到90%以上的识别率.

  11. Investigation of non-premixed flame combustion characters in GO2/GH2 shear coaxial injectors using non-intrusive optical diagnostics

    Science.gov (United States)

    Dai, Jian; Yu, NanJia; Cai, GuoBiao

    2015-12-01

    Single-element combustor experiments are conducted for three shear coaxial geometry configuration injectors by using gaseous oxygen and gaseous hydrogen (GO2/GH2) as propellants. During the combustion process, several spatially and timeresolved non-intrusive optical techniques, such as OH planar laser induced fluorescence (PLIF), high speed imaging, and infrared imaging, are simultaneously employed to observe the OH radical concentration distribution, flame fluctuations, and temperature fields. The results demonstrate that the turbulent flow phenomenon of non-premixed flame exhibits a remarkable periodicity, and the mixing ratio becomes a crucial factor to influence the combustion flame length. The high speed and infrared images have a consistent temperature field trend. As for the OH-PLIF images, an intuitionistic local flame structure is revealed by single-shot instantaneous images. Furthermore, the means and standard deviations of OH radical intensity are acquired to provide statistical information regarding the flame, which may be helpful for validation of numerical simulations in future. Parameters of structure configurations, such as impinging angle and oxygen post thickness, play an important role in the reaction zone distribution. Based on a successful flame contour extraction method assembled with non-linear anisotropic diffusive filtering and variational level-set, it is possible to implement a fractal analysis to describe the fractal characteristics of the non-premixed flame contour. As a result, the flame front cannot be regarded as a fractal object. However, this turbulent process presents a self-similarity characteristic.

  12. A method for the evaluation of image quality according to the recognition effectiveness of objects in the optical remote sensing image using machine learning algorithm.

    Directory of Open Access Journals (Sweden)

    Tao Yuan

    Full Text Available Objective and effective image quality assessment (IQA is directly related to the application of optical remote sensing images (ORSI. In this study, a new IQA method of standardizing the target object recognition rate (ORR is presented to reflect quality. First, several quality degradation treatments with high-resolution ORSIs are implemented to model the ORSIs obtained in different imaging conditions; then, a machine learning algorithm is adopted for recognition experiments on a chosen target object to obtain ORRs; finally, a comparison with commonly used IQA indicators was performed to reveal their applicability and limitations. The results showed that the ORR of the original ORSI was calculated to be up to 81.95%, whereas the ORR ratios of the quality-degraded images to the original images were 65.52%, 64.58%, 71.21%, and 73.11%. The results show that these data can more accurately reflect the advantages and disadvantages of different images in object identification and information extraction when compared with conventional digital image assessment indexes. By recognizing the difference in image quality from the application effect perspective, using a machine learning algorithm to extract regional gray scale features of typical objects in the image for analysis, and quantitatively assessing quality of ORSI according to the difference, this method provides a new approach for objective ORSI assessment.

  13. 光学遥感舰船目标识别方法%Method for ship recognition using optical remote sensing data

    Institute of Scientific and Technical Information of China (English)

    杜春; 孙即祥; 李智勇; 滕书华

    2012-01-01

    提出一种基于粗糙集理论和分层判别回归技术的光学遥感舰船目标识别方法.该方法首先提出新的光学遥感舰船识别特征——面积比编码,并与四类特征组合作为备选特征;然后基于粗糙集理论按同可区分度来计算各备选特征的重要性权值,自动选择出对正确识别贡献较大的特征组合;最后根据分层判别回归原理生成分类判决树来识别光学遥感舰船目标.实验结果表明,本文方法在识别精度和速度方面优于最近邻和支持向量机方法,且通用可行.%A new method for ship recognition using optical remote sensing data based on rough set and hierarchical discriminant regression ( HDR) is presented in this paper. First, a new shape feature called area ratio code ( ARC) is proposed and extracted as a candidate feature. Based on the rough set theory, the common discernibility degree is used to compute the significance weight of each candidate feature and select valid recognition features automatically. Ultimately, a decision tree based on the HDR theory is built to recognize ships in data from optical remote sensing systems. Experimental results on real data show that the proposed method is generalizable and can get better classification rates at a higher speed than the KNN or SVM method.

  14. Reliable Devanagri Handwritten Numeral Recognition using Multiple Classifier and Flexible Zoning Approach

    Directory of Open Access Journals (Sweden)

    Pratibha Singh

    2014-08-01

    Full Text Available A reliability evaluation system for the recognition of Devanagri Numerals is proposed in this paper. Reliability of classification is very important in applications of optical character recognition. As we know that the outliers and ambiguity may affect the performance of recognition system, a rejection measure must be there for the reliable recognition of the pattern. For each character image pre-processing steps like normalization, binarization, noise removal and boundary extraction is performed. After calculating the bounding box features are extracted for each partition of the numeral image. Features are calculated on three different zoning methods. Directional feature is considered which is obtained using chain code and gradient direction quantization of the orientations. The Zoning firstly, is considered made up of uniform partitions and secondly of non-uniform compartments based on the density of the pixels. For classification 1-nearest neighbor based classifier, quadratic bayes classifier and linear bayes classifier are chosen as base classifier. The base classifiers are combined using four decision combination rules namely maximum, Median, Average and Majority Voting. The framework is used to test the reliability of recognition system against ambiguity.

  15. A method of recognition of arabic cursive handwriting.

    Science.gov (United States)

    Almuallim, H; Yamaguchi, S

    1987-05-01

    In spite of the progress of machine recognition techniques of Latin, Kana, and Chinese characters over the two past decades, the machine recognition of Arabic characters has remained almost untouched. In this correspondence, a structural recognition method of Arabic cursively handwritten words is proposed. In this method, words are first segmented into strokes. Those strokes are then classified using their geometrical and topological properties. Finally, the relative position of the classified strokes are examined, and the strokes are combined in several steps into a string of characters that represents the recognized word. Experimental results on texts handwritten by two persons showed high recognition accuracy.

  16. The well-tuned blues: the role of structural colours as optical signals in the species recognition of a local butterfly fauna (Lepidoptera: Lycaenidae: Polyommatinae).

    Science.gov (United States)

    Bálint, Zsolt; Kertész, Krisztián; Piszter, Gábor; Vértesy, Zofia; Biró, László P

    2012-08-01

    The photonic nanoarchitectures responsible for the blue colour of the males of nine polyommatine butterfly species living in the same site were investigated structurally by electron microscopy and spectrally by reflectance spectroscopy. Optical characterization was carried out on 110 exemplars. The structural data extracted by dedicated software and the spectral data extracted by standard software were inputted into an artificial neural network software to test the specificity of the structural and optical characteristics. It was found that both the structural and the spectral data allow species identification with an accuracy better than 90 per cent. The reflectance data were further analysed using a colour representation diagram built in a manner analogous to that of the human Commission Internationale de l'Eclairage diagram, but the additional blue visual pigment of lycaenid butterflies was taken into account. It was found that this butterfly-specific colour representation diagram yielded a much clearer distinction of the position of the investigated species compared with previous calculations using the human colour space. The specific colours of the investigated species were correlated with the 285 flight-period data points extracted from museum collections. The species with somewhat similar colours fly in distinct periods of the year such that the blue colours are well tuned for safe mate/competitor recognition. This allows for the creation of an effective pre-zygotic isolation mechanism for closely related synchronic and syntopic species.

  17. All optical three dimensional spatio-temporal correlator for automatic event recognition using a multiphoton atomic system

    Science.gov (United States)

    Monjur, Mehjabin S.; Fouda, Mohamed F.; Shahriar, Selim M.

    2016-12-01

    We describe an automatic event recognition (AER) system based on a three-dimensional spatio-temporal correlator (STC) that combines the techniques of holographic correlation and photon echo based temporal pattern recognition. The STC is shift invariant in space and time. It can be used to recognize rapidly an event (e.g., a short video clip) that may be present in a large video file, and determine the temporal location of the event. Using polar Mellin transform, it is possible to realize an STC that is also scale and rotation invariant spatially. Numerical simulation results of such a system are presented using quantum mechanical equations of evolution. For this simulation we have used the model of an idealized, decay-free two level system of atoms with an inhomogeneous broadening that is larger than the inverse of the temporal resolution of the data stream. We show how such a system can be realized by using a lambda-type three level system in atomic vapor, via adiabatic elimination of the intermediate state. We have also developed analytically a three dimensional transfer function of the system, and shown that it agrees closely with the results obtained via explicit simulation of the atomic response. The analytical transfer function can be used to determine the response of an STC very rapidly. In addition to the correlation signal, other nonlinear terms appear in the explicit numerical model. These terms are also verified by the analytical model. We describe how the AER can be operated in a manner such that the correlation signal remains unaffected by the additional nonlinear terms. We also show how such a practical STC can be realized using a combination of a porous-glass based Rb vapor cell, a holographic video disc, and a lithium niobate crystal.

  18. Radical Knowledge and Character Learning among Learners of Chinese as a Foreign Languag

    Institute of Scientific and Technical Information of China (English)

    Helen H. Shen

    2000-01-01

    This study investigates the relationship of radical knowledge to recognition and production of novel phonetic-semantic compound characters among learners of Chinese as a foreign language. The subjects are 40 first- and second-year college students in Chinese classes. The result indicates that students' knowledge of radicals played an important role in their recognition of novel morphologically transparent compound characters, but not in morphologically opaque characters. The result also shows that students with good radical knowledge perform significantly better in production of novel morphological transparent characters than do students with poor radical knowledge.

  19. Recognizing Chinese characters in digital ink from non-native language writers using hierarchical models

    Science.gov (United States)

    Bai, Hao; Zhang, Xi-wen

    2017-06-01

    While Chinese is learned as a second language, its characters are taught step by step from their strokes to components, radicals to components, and their complex relations. Chinese Characters in digital ink from non-native language writers are deformed seriously, thus the global recognition approaches are poorer. So a progressive approach from bottom to top is presented based on hierarchical models. Hierarchical information includes strokes and hierarchical components. Each Chinese character is modeled as a hierarchical tree. Strokes in one Chinese characters in digital ink are classified with Hidden Markov Models and concatenated to the stroke symbol sequence. And then the structure of components in one ink character is extracted. According to the extraction result and the stroke symbol sequence, candidate characters are traversed and scored. Finally, the recognition candidate results are listed by descending. The method of this paper is validated by testing 19815 copies of the handwriting Chinese characters written by foreign students.

  20. Holistic neural coding of Chinese character forms in bilateral ventral visual system.

    Science.gov (United States)

    Mo, Ce; Yu, Mengxia; Seger, Carol; Mo, Lei

    2015-02-01

    How are Chinese characters recognized and represented in the brain of skilled readers? Functional MRI fast adaptation technique was used to address this question. We found that neural adaptation effects were limited to identical characters in bilateral ventral visual system while no activation reduction was observed for partially overlapping characters regardless of the spatial location of the shared sub-character components, suggesting highly selective neuronal tuning to whole characters. The consistent neural profile across the entire ventral visual cortex indicates that Chinese characters are represented as mutually distinctive wholes rather than combinations of sub-character components, which presents a salient contrast to the left-lateralized, simple-to-complex neural representations of alphabetic words. Our findings thus revealed the cultural modulation effect on both local neuronal activity patterns and functional anatomical regions associated with written symbol recognition. Moreover, the cross-language discrepancy in written symbol recognition mechanism might stem from the language-specific early-stage learning experience.

  1. Reading pixelized paragraphs of Chinese characters using simulated prosthetic vision.

    Science.gov (United States)

    Zhao, Ying; Lu, Yanyu; Zhao, Ji; Wang, Kaihu; Ren, Qiushi; Wu, Kaijie; Chai, Xinyu

    2011-07-29

    Visual prostheses offer a possibility of restoring useful reading ability to the blind. The psychophysics of simulating reading with a prosthesis using pixelized text has attracted attention recently. This study was an examination of the reading accuracy and efficiency of pixelized Chinese paragraphs after different parameters were altered. Forty native Chinese speakers with normal or corrected visual acuity (20/20) participated in four experiments. Reading accuracy and efficiency were measured after changing the character resolution, character size, pixel dropout percentage, number of gray levels, and luminance. A 5° × 5° character appeared to be the optimal size necessary for accurate pixelized reading. Reading accuracy close to 100% could be achieved with 10 × 10 pixels/character and ∼60% with a 6 × 6 pixel resolution. Pixel dropout adversely affected accuracy, and paragraphs with a 50% dropout were unreadable. Luminance had little effect; however, the number of gray levels significantly affected reading performance. Paragraph reading was at least 5% more accurate at each resolution than was the accuracy of Chinese character recognition. Character size and resolution, pixel dropout, and the number of gray levels clearly affected the reading performance of pixelized Chinese paragraphs. Compared with pixelized character recognition, pixelized Chinese paragraph reading achieved higher accuracy; thus, optimal Chinese reading performance may require prostheses with more electrodes (1000) than are required to read paragraphs in the Latin alphabet (500).

  2. Dynamically reconfigurable multiple beam illumination based on optical correlation

    DEFF Research Database (Denmark)

    Glückstad, Jesper; Palima, Darwin; Dam, Jeppe Seidelin

    2009-01-01

    We adapt concepts from optical correlation and optical pattern recognition to propose a method for generating reconfigurable multiple spots with high efficiency. The generated spots correspond to the correlation spikes in optical pattern recognition. In pattern recognition, optimizing the correla...

  3. Real-time optical multiple-object recognition and tracking demonstration: A friendly challenge to the digital field

    Science.gov (United States)

    Chao, Tien-Hsin; Liu, Hua-Kuang

    1980-01-01

    Researchers demonstrated the first optical multiple object tracking system. The system is capable of simultaneous tracking of multiple objects, each with independent movements in real-time, limited only to the TV frame rate (30 msec). In order to perform a similar tracking operation, a large computer system and very complex software would be needed. Although researchers have demonstrated the tracking of only 3 objects, the system capacity can easily be expanded by 2 orders of magnitude.

  4. About Chinese Characters

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    It is perhaps a facet of human nature that makes a person want to beking, and to control others. The character "王" was originally"王",symbolizing the emerald prayer beads worn exclusively by the king. Inthe course of this character’s evolution, however, new connotations were

  5. About Chinese Characters

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    Some Chinese characters refer to natural phenomena andsubstances, such as "雨" yu (rain), "云" yun (clouds), "雪" xue (snow),"电" dian (lightning) and "雷" lei (thunder). The original form of "雨"was"(?)," in which"(?)" represents the cloud layer, and"(?)"symbolizes rain drops.

  6. The typeface character

    DEFF Research Database (Denmark)

    Beier, Sofie

    2015-01-01

    Research from the fields of neuroscience and psychology, shows that typefaces can carry different semantic associations. However, to be able to read a text, the reader can no longer focus on the character of the typeface, as the human mind is incapable of simultaneously giving full attention...

  7. About Chinese Characters

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    Sheep generally have a cute and docile appearance, which isrepresented by the Chinese character "羊" yang (sheep). The originalform of "羊" was "(?)" , representing a sheep’s head. Later, combinedwith other parts representing sheep’s horns, ears, legs, and tail, it evolvedinto "(?)"、"(?)"、"(?)" and "羊".

  8. Character and Moral Development.

    Science.gov (United States)

    Denton, Johnnie

    1997-01-01

    Reflects on the ways in which children develop character as well as ways to foster moral development in elementary education communities. Includes a brief discussion of Robert Coles' documentation of moral intelligence in children, and lists several ways to aid the moral life of children in Montessori classrooms. (EV)

  9. Whole-book recognition.

    Science.gov (United States)

    Xiu, Pingping; Baird, Henry S

    2012-12-01

    Whole-book recognition is a document image analysis strategy that operates on the complete set of a book's page images using automatic adaptation to improve accuracy. We describe an algorithm which expects to be initialized with approximate iconic and linguistic models--derived from (generally errorful) OCR results and (generally imperfect) dictionaries--and then, guided entirely by evidence internal to the test set, corrects the models which, in turn, yields higher recognition accuracy. The iconic model describes image formation and determines the behavior of a character-image classifier, and the linguistic model describes word-occurrence probabilities. Our algorithm detects "disagreements" between these two models by measuring cross entropy between 1) the posterior probability distribution of character classes (the recognition results resulting from image classification alone) and 2) the posterior probability distribution of word classes (the recognition results from image classification combined with linguistic constraints). We show how disagreements can identify candidates for model corrections at both the character and word levels. Some model corrections will reduce the error rate over the whole book, and these can be identified by comparing model disagreements, summed across the whole book, before and after the correction is applied. Experiments on passages up to 180 pages long show that when a candidate model adaptation reduces whole-book disagreement, it is also likely to correct recognition errors. Also, the longer the passage operated on by the algorithm, the more reliable this adaptation policy becomes, and the lower the error rate achieved. The best results occur when both the iconic and linguistic models mutually correct one another. We have observed recognition error rates driven down by nearly an order of magnitude fully automatically without supervision (or indeed without any user intervention or interaction). Improvement is nearly monotonic, and

  10. Pattern recognition

    CERN Document Server

    Theodoridis, Sergios

    2003-01-01

    Pattern recognition is a scientific discipline that is becoming increasingly important in the age of automation and information handling and retrieval. Patter Recognition, 2e covers the entire spectrum of pattern recognition applications, from image analysis to speech recognition and communications. This book presents cutting-edge material on neural networks, - a set of linked microprocessors that can form associations and uses pattern recognition to ""learn"" -and enhances student motivation by approaching pattern recognition from the designer's point of view. A direct result of more than 10

  11. Chinese Character Acquisition and Visual Skills in Two Chinese Scripts

    Science.gov (United States)

    Mcbride-Chang, Catherine; Chow, Bonnie W. Y.; Zhong, Yiping; Burgess, Stephen; Hayward, William G.

    2005-01-01

    Three different visual skills, along with Chinese character recognition, vocabulary, speeded naming, and syllable deletion skills were tested twice over one school year among 118 Hong Kong and 96 Xiangtan, China kindergartners. Results revealed that a task of Visual Spatial Relationships [Gardner, M. F. (1996). "Test of visual-perceptual skills…

  12. Character strengths and virtues

    OpenAIRE

    2015-01-01

    The target of this work is to carry out a critical analysis about some of the underlying epistemological assumptions in Peterson and Seligman’s book Character Strengths and Virtues. A handbook and classifications (2004). This is a theoretical investigation that belongs to the epistemology of psychology field. According to the theory proposed by Serroni Copello (2003), a critic progress rational criterion is methodologically applied. The analysis points out some epistemological weakness that l...

  13. An Efficient Character Segmentation Based on VNP Algorithm

    Directory of Open Access Journals (Sweden)

    S. Chitrakala

    2012-12-01

    Full Text Available Character segmentation is an important preprocessing stage in image processing applications such as OCR, License Plate Recognition, electronic processing of checks in banks, form processing and, label and barcode recognition. It is essential to have an efficient character segmentation technique because it affects the performance of all the processes that follow and hence, the overall system accuracy. Vertical projection profile is the most common segmentation technique. However, the segmentation results are not always correct in cases where pixels of adjacent characters fall on the same scan line and a minimum threshold is not observed in the histogram to segment the respective adjacent characters. In this study, a character segmentation technique based on Visited Neighbor Pixel (VNP Algorithm is proposed, which is an improvement to the vertical projection profile technique. VNP Algorithm performs segmentation based on the connectedness of the pixels on the scan line with that of the previously visited pixels. Therefore, a clear line of separation is found even when the threshold between two adjacent characters is not minimal. The segmentation results of the traditional vertical projection profile and the proposed method are compared with respect to a few selected fonts and the latter, with an average accuracy of approximately 94%, has shown encouraging results.

  14. Fuzzy logic and optical correlation-based face recognition method for patient monitoring application in home video surveillance

    Science.gov (United States)

    Elbouz, Marwa; Alfalou, Ayman; Brosseau, Christian

    2011-06-01

    Home automation is being implemented into more and more domiciles of the elderly and disabled in order to maintain their independence and safety. For that purpose, we propose and validate a surveillance video system, which detects various posture-based events. One of the novel points of this system is to use adapted Vander-Lugt correlator (VLC) and joint-transfer correlator (JTC) techniques to make decisions on the identity of a patient and his three-dimensional (3-D) positions in order to overcome the problem of crowd environment. We propose a fuzzy logic technique to get decisions on the subject's behavior. Our system is focused on the goals of accuracy, convenience, and cost, which in addition does not require any devices attached to the subject. The system permits one to study and model subject responses to behavioral change intervention because several levels of alarm can be incorporated according different situations considered. Our algorithm performs a fast 3-D recovery of the subject's head position by locating eyes within the face image and involves a model-based prediction and optical correlation techniques to guide the tracking procedure. The object detection is based on (hue, saturation, value) color space. The system also involves an adapted fuzzy logic control algorithm to make a decision based on information given to the system. Furthermore, the principles described here are applicable to a very wide range of situations and robust enough to be implementable in ongoing experiments.

  15. A novel framework for Farsi and latin script identification and Farsi handwritten digit recognition

    Directory of Open Access Journals (Sweden)

    Behrad Alireza

    2010-01-01

    Full Text Available Optical character recognition is an important task for converting handwritten and printed documents to digital format. In multilingual systems, a necessary process before OCR algorithm is script identification. In this paper novel methods for the script language identification and the recognition of Farsi handwritten digits are proposed. Our method for script identification is based on curvature scale space features. The proposed features are rotation and scale invariant and can be used to identify scripts with different fonts. We assumed that the bilingual scripts may have Farsi and English words and characters together; therefore the algorithm is designed to be able to recognize scripts in the connected components level. The output of the recognition is then generalized to word, line and page levels. We used cluster based weighted support vector machine for the classification and recognition of Farsi handwritten digits that is reasonably robust against rotation and scaling. The algorithm extracts the required features using principle component analysis (PCA and linear discrimination analysis (LDA algorithms. The extracted features are then classified using a new classification algorithm called cluster based weighted SVM (CBWSVM. The experimental results showed the promise of the algorithms.

  16. Large even order character sums

    CERN Document Server

    Goldmakher, Leo

    2012-01-01

    A classical theorem of Paley asserts the existence of an infinite family of quadratic characters whose character sums become exceptionally large. In this paper, we establish an analogous result for characters of any fixed even order. Previously our bounds were only known under the assumption of the Generalized Riemann Hypothesis.

  17. How Iconic Are Chinese Characters?

    Science.gov (United States)

    Luk, Gigi; Bialystok, Ellen

    2005-01-01

    The study explores the notion that some Chinese characters contain pictorial indications of meanings that can be used to help retrieve the referent. Thirty adults with no prior knowledge of Chinese guessed the meanings of twenty Chinese characters by choosing between one of two photographs. Half of the characters were considered to be iconic and…

  18. Closed surfaces and character varieties

    CERN Document Server

    Chesebro, Eric

    2012-01-01

    The powerful character variety techniques of Culler and Shalen can be used to find essential surfaces in knot manifolds. We show that module structures on the coordinate ring of the character variety can be used to identify detected boundary slopes as well as when closed surfaces are detected. This approach also yields new number theoretic invariants for the character varieties of knot manifolds.

  19. Optics

    CERN Document Server

    Fincham, W H A

    2013-01-01

    Optics: Ninth Edition Optics: Ninth Edition covers the work necessary for the specialization in such subjects as ophthalmic optics, optical instruments and lens design. The text includes topics such as the propagation and behavior of light; reflection and refraction - their laws and how different media affect them; lenses - thick and thin, cylindrical and subcylindrical; photometry; dispersion and color; interference; and polarization. Also included are topics such as diffraction and holography; the limitation of beams in optical systems and its effects; and lens systems. The book is recommen

  20. The characteristics of event related potential in the cognitive course of individual Chinese characters.

    Science.gov (United States)

    Mingshi, Wang; Hongqiang, Yu; Huisheng, Lu

    2005-01-01

    The difference between the Chinese and English character recognition process and the characteristics of Chinese character recognition process are investigated by analyzing the ERP difference between the matched and mismatched ending strokes of a single Chinese character. First, the P300 are observed in the mismatched ERP waveforms, which don't exist in the matched ERP waveforms (Ppictograph Chinese characters are not only affected by the semanteme, but also closely related to its image of the figure. Secondly, the amplitude of the N400 in the mismatched ending strokes of Chinese character is obviously higher than that in the matched groups (P<0.05). The N400 is distributed in the other areas except the right side of temporal lobe and is higher in the left side. However, the amplitude of N400 in the waveforms has no obvious distinction between the cerebral hemispheres, where the amplitude of N400 are obtained by distracting the ERP of the mismatched individual Chinese character by the ERP of the matched group. These results show that the difference between cerebral hemispheres is attributed to the formal and phonic processing, not due to the semantic processing, which verify that the left and right cerebral hemisphere are both used in the Chinese character recognition, which is very different from the English character recognition, where the left side cerebral hemisphere is used with high percentage.

  1. Periods of Hecke characters

    CERN Document Server

    Schappacher, Norbert

    1988-01-01

    The starting point of this Lecture Notes volume is Deligne's theorem about absolute Hodge cycles on abelian varieties. Its applications to the theory of motives with complex multiplication are systematically reviewed. In particular, algebraic relations between values of the gamma function, the so-called formula of Chowla and Selberg and its generalization and Shimura's monomial relations among periods of CM abelian varieties are all presented in a unified way, namely as the analytic reflections of arithmetic identities beetween Hecke characters, with gamma values corresponding to Jacobi sums. The last chapter contains a special case in which Deligne's theorem does not apply.

  2. Optics

    CERN Document Server

    Fincham, W H A

    2013-01-01

    Optics: Eighth Edition covers the work necessary for the specialization in such subjects as ophthalmic optics, optical instruments and lens design. The text includes topics such as the propagation and behavior of light; reflection and refraction - their laws and how different media affect them; lenses - thick and thin, cylindrical and subcylindrical; photometry; dispersion and color; interference; and polarization. Also included are topics such as diffraction and holography; the limitation of beams in optical systems and its effects; and lens systems. The book is recommended for engineering st

  3. System recognizing Bahamian license plate with touching characters

    Science.gov (United States)

    Dun, Jingyu; Zhang, Sanyuan; Ye, Xiuzi; Zhang, Yin

    2016-11-01

    Various methods are proposed for license plate recognition, but none of them are universal. Some common methods for license plate localization, character extraction, and recognition are analyzed. Then a system is proposed to recognize the Bahamian license plate with touching characters. A vertical edge-based method with a modified sliding window technique is used to locate the license plate, and a machine learning process is used to trim the region. The located license plate is rectified by using the minimum enclosing box and the stroke width value. Then the vertical projection and pairs of extreme points are combined to segment the characters. Finally, a deep learning method is used to recognize the characters. 2996 images are experimented on and the total recognition accuracy achieves 83.29%. Typical methods of each stage are implemented to compare with the proposed methods. In addition, the proposed system is experimented on a public dataset to show the generalization ability of the system. The experimental results show that the proposed system performs better than the other methods and is able to be used in a real-time application.

  4. New performance evaluation models for character detection in images

    Science.gov (United States)

    Wang, YanWei; Ding, XiaoQing; Liu, ChangSong; Wang, Kongqiao

    2010-02-01

    Detection of characters regions is a meaningful research work for both highlighting region of interest and recognition for further information processing. A lot of researches have been performed on character localization and extraction and this leads to the great needs of performance evaluation scheme to inspect detection algorithms. In this paper, two probability models are established to accomplish evaluation tasks for different applications respectively. For highlighting region of interest, a Gaussian probability model, which simulates the property of a low-pass Gaussian filter of human vision system (HVS), was constructed to allocate different weights to different character parts. It reveals the greatest potential to describe the performance of detectors, especially, when the result detected is an incomplete character, where other methods cannot effectively work. For the recognition destination, we also introduced a weighted probability model to give an appropriate description for the contribution of detection results to final recognition results. The validity of performance evaluation models proposed in this paper are proved by experiments on web images and natural scene images. These models proposed in this paper may also be able to be applied in evaluating algorithms of locating other objects, like face detection and more wide experiments need to be done to examine the assumption.

  5. 2—D EAG Method for the Reognition of Hand—Printed Chinese Characters

    Institute of Scientific and Technical Information of China (English)

    赵明

    1990-01-01

    A method,called Two-Dimensional Extended Attribute Grammars(2-D EAGs) for the recognition of hand-printed Chinese characters is presented.This method uses directly two dimensional information,and provides a scheme for dealing with various kinds of specific cases in a uniform way.In this method,components are drawn in guided and redundant way and reductions are made level by leve just in accordance with the component combination relations of Chinese characters.The method provids also polysemous grammars,coexisting grammars and structure inferrings whih constrain redundant recognition by comparison among similar characters of components and greatly increase the tolerance ability to distortion.

  6. The effect of character contextual diversity on eye movements in Chinese sentence reading.

    Science.gov (United States)

    Chen, Qingrong; Zhao, Guoxia; Huang, Xin; Yang, Yiming; Tanenhaus, Michael K

    2017-03-30

    Chen, Huang, et al. (Psychonomic Bulletin & Review, 2017) found that when reading two-character Chinese words embedded in sentence contexts, contextual diversity (CD), a measure of the proportion of texts in which a word appears, affected fixation times to words. When CD is controlled, however, frequency did not affect reading times. Two experiments used the same experimental designs to examine whether there are frequency effects of the first character of two-character words when CD is controlled. In Experiment 1, yoked triples of characters from a control group, a group matched for character CD that is lower in frequency, and a group matched in frequency with the control group, but higher in character CD, were rotated through the same sentence frame. In Experiment 2 each character from a larger set was embedded in a separate sentence frame, allowing for a larger difference in log frequency compared to Experiment 1 (0.8 and 0.4, respectively). In both experiments, early and later eye movement measures were significantly shorter for characters with higher CD than for characters with lower CD, with no effects of character frequency. These results place constraints on models of visual word recognition and suggest ways in which Chinese can be used to tease apart the nature of context effects in word recognition and language processing in general.

  7. Phoneme Based Speaker—Independent English Command Recognition

    Institute of Scientific and Technical Information of China (English)

    贲俊; 万旺根; 余小清

    2003-01-01

    In this paper we propose a new algorithm of phoneme based speaker-independent English command recognition and develop a speaker-independent English command recognition system. It accelerates the whole system development by using HTK (hide Markov toolkits) and Visual C + + based on the character' istics of speaker-independent speech recognition. In recognition phase we combine the confidence measures with incomplete matching, which considerably improve the quality of recognition. The recognition accuracyis increased by 4.8 % over complete matching without back-end processing when the sige of vocabulary is more than 10.

  8. Psychopathic characters in fiction.

    Science.gov (United States)

    Piechowski-Jozwiak, Bartlomiej; Bogousslavsky, Julien

    2013-01-01

    The theme of psychopathy has fascinated artists and the general public for centuries. The first concepts on psychopathy came from the parasciences, such as phrenology where anatomical features were linked to certain psychopathic/immoral behaviors. The concept of psychopathy was recognized by forensic psychiatry a few decades ago and this official recognition was followed by the emergence of scientific and clinical guidelines for the diagnosis and prognosis of psychopaths. These modern tools can also be used for historical purposes by allowing us to look back on fictional works and identify psychopaths in literature. Interpretation of fictitious psychopaths needs to be related to the historical situation in which the novels were written; such investigations can be both enriching and thrilling.

  9. Maya Studio Projects Photorealistic Characters

    CERN Document Server

    Palamar, Todd

    2011-01-01

    Create realistic characters with Maya tools and this project-based book Maya character generation tools are extremely sophisticated, and there's no better way to learn all their capabilities than by working through the projects in this hands-on book. This official guide focuses on understanding and implementing Maya's powerful tools for creating realistic characters for film, games, and TV. Use a variety of tools to create characters from skeleton to clothing, including hairstyles and facial hair, and learn how to use Performance Capture. A DVD includes supplementary videos, project support fi

  10. Bounds for Certain Character Sums

    Institute of Scientific and Technical Information of China (English)

    杨锦; 郑志勇

    2003-01-01

    This paper shows a connection between exponential sums and character sums. In particular, we introduce a character sum that is an analog of the classical Kloosterman sums and establish the analogous Weil-Estermann's upper bound for it. The paper also analyzes a generalized Hardy-Littlewood example for character sums, which shows that the upper bounds given here are the best possible. The analysis makes use of local bounds for the exponential sums and character sums. The basic theorems have been previously established.

  11. Machine Recognition Of Cursive Arabic Words

    Science.gov (United States)

    Amin, Adnan; Masini, Gerald

    1983-03-01

    We present the IRAC II (Interactive Recognition of Arabic Characters) and the IRAC III systems, which recognize isolated Arabic words written from right to left on a graphic tablet connected to a mini-computer (MITRA 15125). In the IRAC II version words are recognized following their segmentation into characters. The IRAC III version uses global recognition with no segmentation. It calculates a vector defining the main parameters for each stroke making up the word and uses this information to recognize the word by dictionary consultation. It resolves eventual ambiguities with the help of secondary parameters calculated for each stroke.

  12. 基于AdaBoost算法和光流匹配的实时手势识别%Real-time Gesture Recognition Based on AdaBoost Algorithm and Optical Flow Matching

    Institute of Scientific and Technical Information of China (English)

    王凯; 于鸿洋; 张萍

    2012-01-01

    着眼于更宽泛和更便捷的应用需要,提出了基于AdaBoost算法和光流匹配的实时手势识别方案.只需连接到计算机的摄像头读取二维手势视频片段就能对手势作为较为准确的识别.其中,采用AdaBoost算法遍历图像,完成静态手势的识别工作;在动态手势的识别过程中,运用了光流法结合模板匹配的方法.整个系统对静态和动态手势的识别均具有较强的鲁棒性.%Focusing on more general and more convenient application, a novel real-time gesture recognition method based on AdaBoost algorithm and optical flow matching was put forward. In detail, the AdaBoost algorithm was used to traverse the whole image for the recognition of static gestures. As to the dynamic gestures, the method combining optical flow with template matching was utilized. The whole system has strong robustness in the recognition of both static and dynamic gestures.

  13. Character strengths and virtues

    Directory of Open Access Journals (Sweden)

    Mariana Gancedo

    2015-09-01

    Full Text Available The target of this work is to carry out a critical analysis about some of the underlying epistemological assumptions in Peterson and Seligman’s book Character Strengths and Virtues. A handbook and classifications (2004. This is a theoretical investigation that belongs to the epistemology of psychology field. According to the theory proposed by Serroni Copello (2003, a critic progress rational criterion is methodologically applied. The analysis points out some epistemological weakness that leads to incongruences in the statements and conclusions of the investigations, such as: the absence of a unified theory, a candid search of objectivity, and the superposition of implicit paradigms. It also takes notice of a causal and elementary logic -which goes against today’s scientific paradigm-, and the strong American culture zeitgeist present in the principles of Positive Psychology. Finally, some ethic problems are displayed, in particular the step taken from a descriptive attitude –characteristic of science- toward a prescriptive attitude –characteristic of moral codes-. 

  14. Optical processing

    Science.gov (United States)

    Gustafson, S. C.

    1985-12-01

    The technical contributions were as follows: (1) Optical parallel 2-D neighborhood processor and optical processor assessment technique; (2) High accuracy with moderately accurate components and optical fredkin gate architectures; (3) Integrated optical threshold computing, pipelined polynomial processor, and all optical analog/digital converter; (4) Adaptive optical associative memory model with attention; (5) Effectiveness of parallelism and connectivity in optical computers; (6) Optical systolic array processing using an integrated acoustooptic module; (7) Optical threshold elements and networks, holographic threshold processors, adaptive matched spatial filtering, and coherence theory in optical computing; (8) Time-varying optical processing for sub-pixel targets, optical Kalman filtering, and adaptive matched filtering; (9) Optical degrees of freedom, ultra short optical pulses, number representations, content-addressable-memory processors, and integrated optical Givens rotation devices; (10) Optical J-K flip flop analysis and interfacing for optical computers; (11) Matrix multiplication algorithms and limits of incoherent optical computers; (12) Architecture for machine vision with sensor fusion, pattern recognition functions, and neural net implementations; (13) Optical computing algorithms, architectures, and components; and (14) Dynamic optical interconnections, advantages and architectures.

  15. Development of Portable Automatic Number Plate Recognition System on Android Mobile Phone

    Science.gov (United States)

    Mutholib, Abdul; Gunawan, Teddy S.; Chebil, Jalel; Kartiwi, Mira

    2013-12-01

    The Automatic Number Plate Recognition (ANPR) System has performed as the main role in various access control and security, such as: tracking of stolen vehicles, traffic violations (speed trap) and parking management system. In this paper, the portable ANPR implemented on android mobile phone is presented. The main challenges in mobile application are including higher coding efficiency, reduced computational complexity, and improved flexibility. Significance efforts are being explored to find suitable and adaptive algorithm for implementation of ANPR on mobile phone. ANPR system for mobile phone need to be optimize due to its limited CPU and memory resources, its ability for geo-tagging image captured using GPS coordinates and its ability to access online database to store the vehicle's information. In this paper, the design of portable ANPR on android mobile phone will be described as follows. First, the graphical user interface (GUI) for capturing image using built-in camera was developed to acquire vehicle plate number in Malaysia. Second, the preprocessing of raw image was done using contrast enhancement. Next, character segmentation using fixed pitch and an optical character recognition (OCR) using neural network were utilized to extract texts and numbers. Both character segmentation and OCR were using Tesseract library from Google Inc. The proposed portable ANPR algorithm was implemented and simulated using Android SDK on a computer. Based on the experimental results, the proposed system can effectively recognize the license plate number at 90.86%. The required processing time to recognize a license plate is only 2 seconds on average. The result is consider good in comparison with the results obtained from previous system that was processed in a desktop PC with the range of result from 91.59% to 98% recognition rate and 0.284 second to 1.5 seconds recognition time.

  16. An Automatic Number Plate Recognition System under Image Processing

    OpenAIRE

    Sarbjit Kaur

    2016-01-01

    Automatic Number Plate Recognition system is an application of computer vision and image processing technology that takes photograph of vehicles as input image and by extracting their number plate from whole vehicle image , it display the number plate information into text. Mainly the ANPR system consists of 4 phases: - Acquisition of Vehicle Image and Pre-Processing, Extraction of Number Plate Area, Character Segmentation and Character Recognition. The overall accuracy and efficiency of whol...

  17. BACS: The Brussels Artificial Character Sets for studies in cognitive psychology and neuroscience.

    Science.gov (United States)

    Vidal, Camille; Content, Alain; Chetail, Fabienne

    2017-01-27

    Written symbols such as letters have been used extensively in cognitive psychology, whether to understand their contributions to written word recognition or to examine the processes involved in other mental functions. Sometimes, however, researchers want to manipulate letters while removing their associated characteristics. A powerful solution to do so is to use new characters, devised to be highly similar to letters, but without the associated sound or name. Given the growing use of artificial characters in experimental paradigms, the aim of the present study was to make available the Brussels Artificial Character Sets (BACS): two full, strictly controlled, and portable sets of artificial characters for a broad range of experimental situations.

  18. Bounding the Probability of Error for High Precision Recognition

    CERN Document Server

    Kae, Andrew; Learned-Miller, Erik

    2009-01-01

    We consider models for which it is important, early in processing, to estimate some variables with high precision, but perhaps at relatively low rates of recall. If some variables can be identified with near certainty, then they can be conditioned upon, allowing further inference to be done efficiently. Specifically, we consider optical character recognition (OCR) systems that can be bootstrapped by identifying a subset of correctly translated document words with very high precision. This "clean set" is subsequently used as document-specific training data. While many current OCR systems produce measures of confidence for the identity of each letter or word, thresholding these confidence values, even at very high values, still produces some errors. We introduce a novel technique for identifying a set of correct words with very high precision. Rather than estimating posterior probabilities, we bound the probability that any given word is incorrect under very general assumptions, using an approximate worst case ...

  19. Character Education: Christian Education Perspectives

    Science.gov (United States)

    Wilhelm, Gretchen M.; Firmin, Michael W.

    2008-01-01

    Character is defined broadly by leading authorities, including concepts such as practicing apt behavior and teaching right from wrong. Virtue and moral undertones tend to pervade most experts' use of character, although in secular settings, the notion of ethics is more prominent. Overall, developing in students a desire for the good is how most…

  20. Chinese license plate character segmentation using multiscale template matching

    Science.gov (United States)

    Tian, Jiangmin; Wang, Guoyou; Liu, Jianguo; Xia, Yuanchun

    2016-09-01

    Character segmentation (CS) plays an important role in automatic license plate recognition and has been studied for decades. A method using multiscale template matching is proposed to settle the problem of CS for Chinese license plates. It is carried out on a binary image integrated from maximally stable extremal region detection and Otsu thresholding. Afterward, a uniform harrow-shaped template with variable length is designed, by virtue of which a three-dimensional matching space is constructed for searching of candidate segmentations. These segmentations are detected at matches with local minimum responses. Finally, the vertical boundaries of each single character are located for subsequent recognition. Experiments on a data set including 2349 license plate images of different quality levels show that the proposed method can achieve a higher accuracy at comparable time cost and is robust to images in poor conditions.

  1. Facial Recognition

    National Research Council Canada - National Science Library

    Mihalache Sergiu; Stoica Mihaela-Zoica

    2014-01-01

    .... From birth, faces are important in the individual's social interaction. Face perceptions are very complex as the recognition of facial expressions involves extensive and diverse areas in the brain...

  2. Fingerprint recognition

    OpenAIRE

    Diefenderfer, Graig T.

    2006-01-01

    The use of biometrics is an evolving component in today's society. Fingerprint recognition continues to be one of the most widely used biometric systems. This thesis explores the various steps present in a fingerprint recognition system. The study develops a working algorithm to extract fingerprint minutiae from an input fingerprint image. This stage incorporates a variety of image pre-processing steps necessary for accurate minutiae extraction and includes two different methods of ridge thin...

  3. Recognition of handprinted and cursive words by finding feature correspondences

    Science.gov (United States)

    Hepp, Daniel J.

    1994-03-01

    This paper describes a method for off-line recognition of handprinted and cursive words. The module takes as input a binary word image and a lexicon of strings, and ranks the lexicon according to the likelihood of match to the given word image. To perform recognition, a set of character models is used. The models employ a graph representation. Each character model consists of a set of features in spatial relationship to one another. The character models are automatically built in a clustering process. Character merging is performed by finding the appropriate correspondences between pairs of character sample features. This is accomplished by finding a solution to the assignment problem, which is an O(n3) linear programming algorithm. The end result of the training process is a set of random graph character prototypes for each character class. Because it is not possible to clearly segment the word image into characters before recognition, segmentation and recognition are bound together in a dynamic programming process. Results are presented for a set of word images extracted from mailpieces in the live mailstream.

  4. Preparation of BSA Molecule Surface-imprinted Material and Studies on its Macromolecule Recognition Characters%牛血清白蛋白分子表面印迹材料的制备及其大分子识别特性研究

    Institute of Scientific and Technical Information of China (English)

    史楠; 高保娇; 陈涛

    2014-01-01

    -PDAC/CPVA were characterized by FTIR and SEM.On this basis,the macromolecule recognition character of MIP-PDAC/CPVA microspheres for BAS was examined in depth.The experimental results show that MIP-PDAC/CPVA microspheres possess excellent binding affinity and very high recognition selectivity.The binding capacity of BAS on MIP-PDAC/CPVA microspheres reaches up to 108 mg/g,and the coefficient of selectivity of MIP-PDAC/CPVA towards BAS relative to the constrast protein bovine hemoglobin (BHb) actually gets up to 60.2.

  5. Character theory of finite groups

    CERN Document Server

    Isaacs, I Martin

    2006-01-01

    Character theory is a powerful tool for understanding finite groups. In particular, the theory has been a key ingredient in the classification of finite simple groups. Characters are also of interest in their own right, and their properties are closely related to properties of the structure of the underlying group. The book begins by developing the module theory of complex group algebras. After the module-theoretic foundations are laid in the first chapter, the focus is primarily on characters. This enhances the accessibility of the material for students, which was a major consideration in the

  6. The N2- and N400-like effects of radicals on complex Chinese characters.

    Science.gov (United States)

    Wang, Quanhong; Dong, Yunzhu

    2013-08-26

    Participants were asked to complete a delayed character-matching task, while their event-related brain potentials (ERPs) elicited by Chinese character fragments were recorded. This task required participants to match probe characters with their preceding fragments, which were randomly assigned to be either radical or stroke-deleted. However, the same number of strokes was retained in either case. The stroke-deleted fragments, which contained fewer intact radicals, elicited larger N2- and N400-like components compared with the radical-deleted fragments. Stroke-deleted fragments displayed lower response accuracy than the radical-deleted fragments. These results indicate that simple radicals have an intermediate or sub-character function in Chinese character recognition. The processing of characters with more destroyed radicals is impeded within a multilayer interactive-activation model. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

  7. WORD LEVEL DISCRIMINATIVE TRAINING FOR HANDWRITTEN WORD RECOGNITION

    NARCIS (Netherlands)

    Chen, W.; Gader, P.

    2004-01-01

    Word level training refers to the process of learning the parameters of a word recognition system based on word level criteria functions. Previously, researchers trained lexicon­driven handwritten word recognition systems at the character level individually. These systems generally use statistical o

  8. WORD LEVEL DISCRIMINATIVE TRAINING FOR HANDWRITTEN WORD RECOGNITION

    NARCIS (Netherlands)

    Chen, W.; Gader, P.

    2004-01-01

    Word level training refers to the process of learning the parameters of a word recognition system based on word level criteria functions. Previously, researchers trained lexicon­driven handwritten word recognition systems at the character level individually. These systems generally use statistical

  9. A review on radio based activity recognition

    Directory of Open Access Journals (Sweden)

    Shuangquan Wang

    2015-02-01

    Full Text Available Recognizing human activities in their daily living enables the development and widely usage of human-centric applications, such as health monitoring, assisted living, etc. Traditional activity recognition methods often rely on physical sensors (camera, accelerometer, gyroscope, etc. to continuously collect sensor readings, and utilize pattern recognition algorithms to identify user׳s activities at an aggregator. Though traditional activity recognition methods have been demonstrated to be effective in previous work, they raise some concerns such as privacy, energy consumption and deployment cost. In recent years, a new activity recognition approach, which takes advantage of body attenuation and/or channel fading of wireless radio, has been proposed. Compared with traditional activity recognition methods, radio based methods utilize wireless transceivers in environments as infrastructure, exploit radio communication characters to achieve high recognition accuracy, reduce energy cost and preserve user׳s privacy. In this paper, we divide radio based methods into four categories: ZigBee radio based activity recognition, WiFi radio based activity recognition, RFID radio based activity recognition, and other radio based activity recognition. Some existing work in each category is introduced and reviewed in detail. Then, we compare some representative methods to show their advantages and disadvantages. At last, we point out some future research directions of this new research topic.

  10. Elementary Character Education: Local Perspectives, Echoed Voices.

    Science.gov (United States)

    Nickell, Pat; Field, Sherry L.

    2001-01-01

    Presents information based on a yearlong study of character education in an elementary school that was implementing "Kids with Character." Offers an analysis of the responses by students, teachers, and parents about character, development of character, and the program. Indicates that contemporary character education programs are similar to…

  11. Character as the Aim of Education

    Science.gov (United States)

    Shields, David Light

    2011-01-01

    The aim of education should be developing intellectual character, moral character, civic character, and performance character. That does not mean that schools should ignore teaching content, but that the dispositions and habits of mind that come from developing these four forms of character will remain with students throughout their lives.…

  12. Construct Clinical Research Data Management System by Optical Character Recognition%利用光学识别技术构建临床研究数据管理系统

    Institute of Scientific and Technical Information of China (English)

    文天才; 刘保延; 王建生

    2007-01-01

    利用OCR(光学字符识别)技术替代传统手式录入方式,可提高临床研究中数据管理的质量和效率.临床数据传输识别系统利用OCR技术为临床研究数据管理过程提供整体了整体的解决方案.

  13. Iconic and multi-stroke gesture recognition

    NARCIS (Netherlands)

    Willems, D.J.M.; Niels, R.M.J.; Gerven, M.A.J. van; Vuurpijl, L.G.

    2009-01-01

    Many handwritten gestures, characters, and symbols comprise multiple pendown strokes separated by penup strokes. In this paper, a large number of features known from the literature are explored for the recognition of such multi-stroke gestures. Features are computed from a global gesture shape. From

  14. Mining and modeling character networks

    CERN Document Server

    Bonato, Anthony; Elenberg, Ethan R; Gleich, David F; Hou, Yangyang

    2016-01-01

    We investigate social networks of characters found in cultural works such as novels and films. These character networks exhibit many of the properties of complex networks such as skewed degree distribution and community structure, but may be of relatively small order with a high multiplicity of edges. Building on recent work of beveridge, we consider graph extraction, visualization, and network statistics for three novels: Twilight by Stephanie Meyer, Steven King's The Stand, and J.K. Rowling's Harry Potter and the Goblet of Fire. Coupling with 800 character networks from films found in the http://moviegalaxies.com/ database, we compare the data sets to simulations from various stochastic complex networks models including random graphs with given expected degrees (also known as the Chung-Lu model), the configuration model, and the preferential attachment model. Using machine learning techniques based on motif (or small subgraph) counts, we determine that the Chung-Lu model best fits character networks and we ...

  15. Status of pattern recognition with wavelet analysis

    Institute of Scientific and Technical Information of China (English)

    Yuanyan TANG

    2008-01-01

    Pattern recognition has become one of the fastest growing research topics in the fields of computer science and electrical and electronic engineering in the recent years.Advanced research and development in pattern recognition have found numerous applications in such areas as artificial intelligence,information security,biometrics,military science and technology,finance and economics,weather forecast,image processing,communication,biomedical engineering,document processing,robot vision,transportation,and endless other areas,with many encouraging results.The achievement of pattern recognition is most likely to benefit from some new developments of theoretical mathematics including wavelet analysis.This paper aims at a brief survey of pattern recognition with the wavelet theory.It contains the following respects:analysis and detection of singularities with wavelets;wavelet descriptors for shapes of the objects;invariant representation of patterns;handwritten and printed character recognition;texture analysis and classification;image indexing and retrieval;classification and clustering;document analysis with wavelets;iris pattern recognition;face recognition using wavelet transform;hand gestures classification;character processing with B-spline wavelet transform;wavelet-based image fusion,and others.

  16. Character profiles and life satisfaction.

    Science.gov (United States)

    Park, Hwanjin; Suh, Byung Seong; Kim, Won Sool; Lee, Hye-Kyung; Park, Seon-Cheol; Lee, Kounseok

    2015-04-01

    There is a surge of interest in subjective well-being (SWB), which concerns how individuals feel about their happiness. Life satisfaction tends to be influenced by individual psychological traits and external social factors. The aim of this study was to examine the relationship between individual character and SWB. Data from 3522 university students were analyzed in this study. Character profiles were evaluated using the Temperament and Character Inventory-Revised Short version (TCI-RS). Life satisfaction was assessed using the Satisfaction with Life Scale (SWLS). All statistical tests regarding the correlations between each character profile and life satisfaction were conducted using ANOVAs, t-tests, multiple linear regression models and correlation analyses. The creative (SCT) profile was associated with the highest levels of life satisfaction, whereas the depressive (sct) profile was associated with the lowest levels of life satisfaction. Additionally, high self-directedness, self-transcendence and cooperation were associated with high life satisfaction. The results of gender-adjusted multiple regression analysis showed that the effects of self-directedness were the strongest in the assessment of one's quality of life, followed by self-transcendence and cooperativeness, in that order. All of the three-character profiles were significantly correlated with one's quality of life, and the character profiles of TCI-RS explained 27.6% of life satisfaction in total. Among the three-character profiles, the self-directedness profile was most associated with life satisfaction. Our study was cross-sectional, and self-reported data from students at a single university were analyzed. The results of this study showed that, among the character profiles, the effects of self-directedness were the strongest for predicting life satisfaction. Copyright © 2014 Elsevier Inc. All rights reserved.

  17. Studying Characters in "Romeo and Juliet."

    Science.gov (United States)

    Guinhawa, Wilhelmina

    1994-01-01

    Describes an activity in which high school students who are reading "Romeo and Juliet" compile information on major characters and create a collection of cards similar to sports cards, to help them understand each character and that character's motives. (SR)

  18. Factors affecting results of optical correlation recognition for underwater laser imaging%影响水下距离选通激光图像光学相关识别的若干因素

    Institute of Scientific and Technical Information of China (English)

    姚广涛; 张晓晖; 戴路; 葛卫龙; 韩宏伟

    2012-01-01

    The relationship between the underwater laser imaging and correlation peak output was studied for the application of optical correlation recognition to underwater range-gated laser images. Firstly, the optical recognition peak output efficiency varying with image distortion was analyzed, and the factors leading to image distortion were discussed. Secondly, the phase matching correlation was used to analyze the underwater laser images collected in experiments according to the different system parameters which were set and the joint evaluation of the correlation output with peak value, PCE, Disc and other indicators was adopted to measure the optical correlation recognition performance. MATLAB simulation results show that the single laser pulse energy, ICCD gain, imaging distance and other factors will cause the distortion of the image phase characteristics, and further lower recognition rate. The results can provide a reference for the establishment of the underwater range-gated imaging system control model and the design of matched filter.%针对水下距离选通激光图像光学相关识别技术的应用,研究了引起图像畸变从而导致光学相关识别相关峰输出效率降低的若干因素,并通过实验的方法采集了不同系统参数设置下的激光成像图片,然后采用相位匹配的方法对图片进行相关性分析,同时应用PCE、Disc等指标联合评价输出的相关峰质量,从而衡量各因素所引起的成像畸变对光学相关识别性能的影响程度.MATLAB软件仿真结果证明:激光单脉冲能量、ICCD增益、成像距离等因素变化均会引起图像相位特征畸变,导致相关识别鉴别率降低.该结果可为建立水下距离选通成像系统控制模型和设计匹配滤波器提供参考.

  19. EMPIRICAL STUDY OF CAR LICENSE PLATES RECOGNITION

    Directory of Open Access Journals (Sweden)

    Nasa Zata Dina

    2015-01-01

    Full Text Available The number of vehicles on the road has increased drastically in recent years. The license plate is an identity card for a vehicle. It can map to the owner and further information about vehicle. License plate information is useful to help traffic management systems. For example, traffic management systems can check for vehicles moving at speeds not permitted by law and can also be installed in parking areas to se-cure the entrance or exit way for vehicles. License plate recognition algorithms have been proposed by many researchers. License plate recognition requires license plate detection, segmentation, and charac-ters recognition. The algorithm detects the position of a license plate and extracts the characters. Various license plate recognition algorithms have been implemented, and each algorithm has its strengths and weaknesses. In this research, I implement three algorithms for detecting license plates, three algorithms for segmenting license plates, and two algorithms for recognizing license plate characters. I evaluate each of these algorithms on the same two datasets, one from Greece and one from Thailand. For detecting li-cense plates, the best result is obtained by a Haar cascade algorithm. After the best result of license plate detection is obtained, for the segmentation part a Laplacian based method has the highest accuracy. Last, the license plate recognition experiment shows that a neural network has better accuracy than other algo-rithm. I summarize and analyze the overall performance of each method for comparison.

  20. Object Recognition Using Range Images.

    Science.gov (United States)

    1985-12-01

    with a multiplexed filter which contains a number of rotated and scaled filters (Leib and others, 1978:2892-2899) and (Mendelsohn and Wohlers , 1980...Butler, Steve. "Three Dimensional Pattern Recognition." Unpublished report . Electro-Optical Terminal Guidance Branch, Eglin AFB FL, 1985. Casasent, David...Correlation:Final Report , June 1982-January 1984. Electro-Optical Terminal Guidance Branch, Eglin AFB FL, August 1985. 136 rv Fujil, H. and Y. Ohtsuba

  1. The Influence of Brand Equity Characters on Children's Food Preferences and Choices.

    Science.gov (United States)

    McGale, Lauren Sophie; Halford, Jason Christian Grovenor; Harrold, Joanne Alison; Boyland, Emma Jane

    2016-10-01

    To assess the influence of brand equity characters displayed on food packaging on children's food preferences and choices, 2 studies were conducted. Brand equity characters are developed specifically to represent a particular brand or product. Despite existing literature suggesting that promotional characters influence children's food choices, to date, no research has assessed the influence of brand equity characters specifically. We recruited 209 children 4-8 years of age from schools and childcare centers in the UK. In a mixed-measures design, the children were asked to rate their taste preferences and preferred snack choice for 3 matched food pairs, presented either with or without a brand equity character displayed on packaging. Study 1 addressed congruent food-character associations and study 2 addressed incongruent associations. Participants were also asked to rate their recognition and liking of characters used. Wilcoxon signed-rank tests and χ(2) analyses were used where appropriate. Children were significantly more likely to show a preference for foods with a brand equity character displayed on the packaging compared with a matched food without a brand equity character, for both congruent and incongruent food-character associations. The presence of a brand equity character also significantly influenced the children's within-pair preferences, within-pair choices, and overall snack choice (congruent associations only). Displaying brand equity characters promotes unhealthy food choices in children. The findings are consistent with those of studies exploring other types of promotional characters. In the context of a childhood obesity epidemic, the use of brand equity characters in the promotion of foods high in fat, salt, and sugar to children should be restricted. Copyright © 2016 Elsevier Inc. All rights reserved.

  2. Moral character in the workplace.

    Science.gov (United States)

    Cohen, Taya R; Panter, A T; Turan, Nazli; Morse, Lily; Kim, Yeonjeong

    2014-11-01

    Using two 3-month diary studies and a large cross-sectional survey, we identified distinguishing features of adults with low versus high levels of moral character. Adults with high levels of moral character tend to: consider the needs and interests of others and how their actions affect other people (e.g., they have high levels of Honesty-Humility, empathic concern, guilt proneness); regulate their behavior effectively, specifically with reference to behaviors that have positive short-term consequences but negative long-term consequences (e.g., they have high levels of Conscientiousness, self-control, consideration of future consequences); and value being moral (e.g., they have high levels of moral identity-internalization). Cognitive moral development, Emotionality, and social value orientation were found to be relatively undiagnostic of moral character. Studies 1 and 2 revealed that employees with low moral character committed harmful work behaviors more frequently and helpful work behaviors less frequently than did employees with high moral character, according to their own admissions and coworkers' observations. Study 3 revealed that adults with low moral character committed more delinquent behavior and had more lenient attitudes toward unethical negotiation tactics than did adults with high moral character. By showing that individual differences have consistent, meaningful effects on employees' behaviors, after controlling for demographic variables (e.g., gender, age, income) and basic attributes of the work setting (e.g., enforcement of an ethics code), our results contest situationist perspectives that deemphasize the importance of personality. Moral people can be identified by self-reports in surveys, and these self-reports predict consequential behaviors months after the initial assessment.

  3. Recognition of Historical Records Using Gabor and Zonal Features

    Directory of Open Access Journals (Sweden)

    Soumya A

    2015-08-01

    Full Text Available The paper addresses the automation of the task of an epigraphist in reading and deciphering inscriptions. The automation steps include Pre-processing, Segmentation, Feature Extraction and Recognition. Preprocessing involves, enhancement of degraded ancient document images which is achieved through Spatial filtering methods, followed by binarization of the enhanced image. Segmentation is carried out using Drop Fall and Water Reservoir approaches, to obtain sampled characters. Next Gabor and Zonal features are extracted for the sampled characters, and stored as feature vectors for training. Artificial Neural Network (ANN is trained with these feature vectors and later used for classification of new test characters. Finally the classified characters are mapped to characters of modern form. The system showed good results when tested on the nearly 150 samples of ancient Kannada epigraphs from Ashoka and Hoysala periods. An average Recognition accuracy of 80.2% for Ashoka period and 75.6% for Hoysala period is achieved.

  4. Triggered optical biosensor

    Science.gov (United States)

    Song, Xuedong; Swanson, Basil I.

    2001-10-02

    An optical biosensor is provided for the detection of a multivalent target biomolecule, the biosensor including a substrate having a bilayer membrane thereon, a recognition molecule situated at the surface, the recognition molecule capable of binding with the multivalent target biomolecule, the recognition molecule further characterized as including a fluorescence label thereon and as being movable at the surface and a device for measuring a fluorescence change in response to binding between the recognition molecule and the multivalent target biomolecule.

  5. License Plate Recognition Algorithm for Passenger Cars in Chinese Residential Areas

    Directory of Open Access Journals (Sweden)

    Qingning Niu

    2012-06-01

    Full Text Available This paper presents a solution for the license plate recognition problem in residential community administrations in China. License plate images are pre-processed through gradation, middle value filters and edge detection. In the license plate localization module the number of edge points, the length of license plate area and the number of each line of edge points are used for localization. In the recognition module, the paper applies a statistical character method combined with a structure character method to obtain the characters. In addition, more models and template library for the characters which have less difference between each other are built. A character classifier is designed and a fuzzy recognition method is proposed based on the fuzzy decision-making method. Experiments show that the recognition accuracy rate is up to 92%.

  6. Facial Recognition

    Directory of Open Access Journals (Sweden)

    Mihalache Sergiu

    2014-05-01

    Full Text Available During their lifetime, people learn to recognize thousands of faces that they interact with. Face perception refers to an individual's understanding and interpretation of the face, particularly the human face, especially in relation to the associated information processing in the brain. The proportions and expressions of the human face are important to identify origin, emotional tendencies, health qualities, and some social information. From birth, faces are important in the individual's social interaction. Face perceptions are very complex as the recognition of facial expressions involves extensive and diverse areas in the brain. Our main goal is to put emphasis on presenting human faces specialized studies, and also to highlight the importance of attractiviness in their retention. We will see that there are many factors that influence face recognition.

  7. Introducing Character Animation with Blender

    CERN Document Server

    Mullen, Tony

    2011-01-01

    Introducing Character Animation with Blender, 2nd Edition is written in a friendly but professional tone, with clear descriptions and numerous illustrative screenshots. Throughout the book, tutorials focus on how to accomplish actual animation goals, while illustrating the necessary technical methods along the way. These are reinforced by clear descriptions of how each specific aspect of Blender works and fits together with the rest of the package. By following all the tutorials, the reader will gain all the skills necessary to build and animate a well-modeled, fully-rigged character of their

  8. Constructing Pairs of Compatible Characters

    Institute of Scientific and Technical Information of China (English)

    Mathias Kratzer

    2003-01-01

    Given a finite group X such that both the conjugacy of elements in X and the length of any conjugacy class in X can be decided/computed efficiently,the first algorithm described in this article constructs a uniquely determined sequence of representatives for all the conjugacy classes of X. In particular, based on this sequence, any two characters of different groups isomorphic to X become comparable against each other which is utilized by a second algorithm designed to construct so-called compatible characters of given finite groups G and H having isomorphic subgroups U ≤ G and V ≤ H, respectively.

  9. Mobile-based text recognition from water quality devices

    Science.gov (United States)

    Dhakal, Shanti; Rahnemoonfar, Maryam

    2015-03-01

    Measuring water quality of bays, estuaries, and gulfs is a complicated and time-consuming process. YSI Sonde is an instrument used to measure water quality parameters such as pH, temperature, salinity, and dissolved oxygen. This instrument is taken to water bodies in a boat trip and researchers note down different parameters displayed by the instrument's display monitor. In this project, a mobile application is developed for Android platform that allows a user to take a picture of the YSI Sonde monitor, extract text from the image and store it in a file on the phone. The image captured by the application is first processed to remove perspective distortion. Probabilistic Hough line transform is used to identify lines in the image and the corner of the image is then obtained by determining the intersection of the detected horizontal and vertical lines. The image is warped using the perspective transformation matrix, obtained from the corner points of the source image and the destination image, hence, removing the perspective distortion. Mathematical morphology operation, black-hat is used to correct the shading of the image. The image is binarized using Otsu's binarization technique and is then passed to the Optical Character Recognition (OCR) software for character recognition. The extracted information is stored in a file on the phone and can be retrieved later for analysis. The algorithm was tested on 60 different images of YSI Sonde with different perspective features and shading. Experimental results, in comparison to ground-truth results, demonstrate the effectiveness of the proposed method.

  10. Preparing Surface Anion-imprinted Material Based on Ion Exchange and Surface-initiated Graft-polymerization and Studies on Its Recognition Character%基于离子交换和表面引发接枝聚合制备阴离子表面印迹材料及其识别特性研究

    Institute of Scientific and Technical Information of China (English)

    杜俊玫; 高保娇; 黄小卫; 张永奇; 王明娟

    2012-01-01

    surfaces of silica gel particles.These free radicals initiated the monomer DMC and the crosslinker N,N’-methylene bisacrylamide(MBA) to be graft-copolymerized and crosslinked,and the surface-imprinting of phosphate ion was realized.After removing the template ions,PO43-ion surface-imprinted material IIP-PDMC/SiO2 was obtained.Both permanganate ion,4 MnO-ion,and PO43- ion are isoelectronic bodies.Their chemical structures are similar and their configurations are the same,but their sizes are different.In this work,4 MnO-ion was used as contrast ion,and both static and dynamic methods were adopted to study the binding properties and ion recognition character of IIP-PDMC/SiO2 for PO43-ion.The experiment results show that IIP-PDMC/SiO2 have specific recognition selectivity and excellent binding affinity for PO43-ion,and its selectivity selectivity coefficients for PO43- ion with respect of 4 MnO-ion is 9.58.Besides,IIP-PDMC/SiO2 has excellent elution property,with NaCl solution as eluent,the desorption ratio of PO43- ion reach 99.53% in 20 BV.

  11. Character Interviews Help Bring Literature to Life.

    Science.gov (United States)

    Swindall, Vickie; Cantrell, R. Jeffrey

    1999-01-01

    Describes "Character Interviews," a class activity that guides children, especially reluctant readers, to the meaning of a story through a thoughtful understanding of character as they consider a character's emotions and motives, to respond to a question as that character would. Describes the interview process. Offers sample interviews…

  12. Building Character through Literacy with Children's Literature

    Science.gov (United States)

    Almerico, Gina M.

    2014-01-01

    Character education is described as curriculum specifically developed to teach children about the quality and traits of good character. One means in which children can learn about good character is through the pages of high quality children's literature. In this study, the author defines the characteristics of an effective character development…

  13. Recognition of Handwritten Textual Annotations using Tesseract Open Source OCR Engine for information Just In Time (iJIT)

    CERN Document Server

    Rakshit, Sandip; Ikeda, Hisashi

    2010-01-01

    Objective of the current work is to develop an Optical Character Recognition (OCR) engine for information Just In Time (iJIT) system that can be used for recognition of handwritten textual annotations of lower case Roman script. Tesseract open source OCR engine under Apache License 2.0 is used to develop user-specific handwriting recognition models, viz., the language sets, for the said system, where each user is identified by a unique identification tag associated with the digital pen. To generate the language set for any user, Tesseract is trained with labeled handwritten data samples of isolated and free-flow texts of Roman script, collected exclusively from that user. The designed system is tested on five different language sets with free- flow handwritten annotations as test samples. The system could successfully segment and subsequently recognize 87.92%, 81.53%, 92.88%, 86.75% and 90.80% handwritten characters in the test samples of five different users.

  14. Character Analysis of Jane Eyre

    Institute of Scientific and Technical Information of China (English)

    胡迎春

    2002-01-01

    This thesis analyses Jane Eyre' s character. No matter what Jane met, no matter where she was, she always rebelled against that unfair society, she never gave up to try her best to get free, independent, fair life and true love. By unremitting efforts she finally got dignity, freedom and true love.

  15. THE THERMODYNAMIC CHARACTER OF INFORMATION

    Directory of Open Access Journals (Sweden)

    Popova T.M.

    2010-04-01

    Full Text Available The article includes data concerning application of one of the universal method of the modern science based on fundamental thermodynamic laws to analyze the efficiency of the information processes. The comparison of the information and thermodynamic processes brought the author to the basic conclusion of the energetic character of information.

  16. Shakespeare Live! and Character Counts.

    Science.gov (United States)

    Brookshire, Cathy A.

    This paper discusses a live production of Shakespeare's "Macbeth" (in full costume but with no sets) for all public middle school and high school students in Harrisonburg and Rockingham, Virginia. The paper states that the "Character Counts" issues that are covered in the play are: decision making, responsibility and…

  17. Hamlet and His Melancholy Character

    Institute of Scientific and Technical Information of China (English)

    张洁

    2007-01-01

    @@ What's the theme of hamlet?His tragedies often portray some noble hero who faces the injustice of human life and is caught in a difficult situation whose fate is closely connected with the fate of the whole nation.The heroes have some weaknesses in their characters,which finally lead to their tragic thin falls.

  18. Character Toys as Psychological Tools

    Science.gov (United States)

    Smirnova, Elena O.

    2011-01-01

    The main characteristic of children's play is its mental aspect--the fact that it is based on thoughts and feelings and not on objective reality. During imaginary play, children go beyond the limits of reality, and toys are tools that help them to do this. Children need character toys--toys that play the role of companion or partner--in the early…

  19. The Origin of Chinese Characters

    Institute of Scientific and Technical Information of China (English)

    1999-01-01

    IN ancient Chinese characters,母(pronounced mu)depicts a womanbending on her knees and crossingher hands in front with two points onher chest symbolizing her breasts.The original meaning of 母 is anadult woman who has given birth tochildren,i.e.a mother It was later

  20. Moral Character and Student Aid

    Science.gov (United States)

    Flint, Thomas A.

    2012-01-01

    Thirty years after the creation of federal student financial aid programs through the Higher Education Act of 1965, the link between moral character and student financial aid programs is once again influencing the public policy debate. A careful look at the debate, though, shows that the nature of concerns has shifted. In the past, the question…

  1. The Origin of Chinese Characters

    Institute of Scientific and Technical Information of China (English)

    1999-01-01

    女 (nü) is a pictograph. InChinese it means female, theopposite of male. In ancientChinese, women had low socialstatus which is reflected in theshape of the character. 女 in theOracle-Bone Script looks like a

  2. Electrophysiological evidence of sublexical phonological access in character processing by L2 Chinese learners of L1 alphabetic scripts.

    Science.gov (United States)

    Yum, Yen Na; Law, Sam-Po; Mo, Kwan Nok; Lau, Dustin; Su, I-Fan; Shum, Mark S K

    2016-04-01

    While Chinese character reading relies more on addressed phonology relative to alphabetic scripts, skilled Chinese readers also access sublexical phonological units during recognition of phonograms. However, sublexical orthography-to-phonology mapping has not been found among beginning second language (L2) Chinese learners. This study investigated character reading in more advanced Chinese learners whose native writing system is alphabetic. Phonological regularity and consistency were examined in behavioral responses and event-related potentials (ERPs) in lexical decision and delayed naming tasks. Participants were 18 native English speakers who acquired written Chinese after age 5 years and reached grade 4 Chinese reading level. Behaviorally, regular characters were named more accurately than irregular characters, but consistency had no effect. Similar to native Chinese readers, regularity effects emerged early with regular characters eliciting a greater N170 than irregular characters. Regular characters also elicited greater frontal P200 and smaller N400 than irregular characters in phonograms of low consistency. Additionally, regular-consistent characters and irregular-inconsistent characters had more negative amplitudes than irregular-consistent characters in the N400 and LPC time windows. The overall pattern of brain activities revealed distinct regularity and consistency effects in both tasks. Although orthographic neighbors are activated in character processing of L2 Chinese readers, the timing of their impact seems delayed compared with native Chinese readers. The time courses of regularity and consistency effects across ERP components suggest both assimilation and accommodation of the reading network in learning to read a typologically distinct second orthographic system.

  3. Speaker Recognition

    DEFF Research Database (Denmark)

    Mølgaard, Lasse Lohilahti; Jørgensen, Kasper Winther

    2005-01-01

    Speaker recognition is basically divided into speaker identification and speaker verification. Verification is the task of automatically determining if a person really is the person he or she claims to be. This technology can be used as a biometric feature for verifying the identity of a person...... in applications like banking by telephone and voice mail. The focus of this project is speaker identification, which consists of mapping a speech signal from an unknown speaker to a database of known speakers, i.e. the system has been trained with a number of speakers which the system can recognize....

  4. Handwritten Arabic Numeral Recognition using a Multi Layer Perceptron

    CERN Document Server

    Das, Nibaran; Saha, Sudip; Haque, Syed Sahidul

    2010-01-01

    Handwritten numeral recognition is in general a benchmark problem of Pattern Recognition and Artificial Intelligence. Compared to the problem of printed numeral recognition, the problem of handwritten numeral recognition is compounded due to variations in shapes and sizes of handwritten characters. Considering all these, the problem of handwritten numeral recognition is addressed under the present work in respect to handwritten Arabic numerals. Arabic is spoken throughout the Arab World and the fifth most popular language in the world slightly before Portuguese and Bengali. For the present work, we have developed a feature set of 88 features is designed to represent samples of handwritten Arabic numerals for this work. It includes 72 shadow and 16 octant features. A Multi Layer Perceptron (MLP) based classifier is used here for recognition handwritten Arabic digits represented with the said feature set. On experimentation with a database of 3000 samples, the technique yields an average recognition rate of 94....

  5. CHARACTERS THAT SUFFERED DUE TO SHORTAGE IN THE CHARACTERS

    Directory of Open Access Journals (Sweden)

    Ma Feng

    2010-05-01

    Full Text Available In this article, the theories about motif and type will be used for analyzing the very types ofcharacters that suffered because of the shortages. To begin with, the analyzing of the differences andsimilarities of the shortages of each character will be counted on the inside and outside parts of theirsufferings. Then the theories of Nietzsche’s and of some myths will be used for analyzing the furtherreason of the sufferings. At last, investigating the special value those sufferings have brought forliteratures and for TV series. Multi-angle perspective is useful for investigating the unique charms ofthe shortages of characters as well as for finding out new understandings for the types of sufferings.

  6. A Survey on Recognition of Devnagari Script

    Directory of Open Access Journals (Sweden)

    Ratnashil N Khobragade

    2013-01-01

    Full Text Available This paper describes a set of preprocessing, segmentation, feature extraction, classification and matching techniques, which play very important role in the recognition of characters. Feature extraction provides us methods with the help of which we can identify characters uniquely and with high degree of accuracy. So many approaches have been proposed for pre-processing, feature extraction, learning/classification, and post-processing. The objective of this paper is to review these techniques, so that the set of these techniques can be appreciated.

  7. Development of modified method for text recognition in standardized picture

    OpenAIRE

    Касьян, Константин Николаевич; Братчиков, Владимир Владимирович; Шкарупило, Вадим Викторович

    2015-01-01

    Text recognition in images is a very urgent problem in modern search engines. There are many different methods and techniques for text recognition. The paper is a method for text recognition in a standardized image. Standardized image means an image that has the same font, character size, certain writing order, such as the serial number or license plate of the car.In the paper, we developed an improved method for text recognition in the image. The method consists in a preliminary search of th...

  8. The recognition of work

    OpenAIRE

    Nierling, Linda

    2007-01-01

    The following article argues that recognition structures in work relations differ significantly in the sphere of paid work in contrast to unpaid work in private spheres. According to the systematic approach on recognition of Axel Honneth three different levels of recognition are identified: the interpersonal recognition, organisational recognition and societal recognition. Based on this framework it can be stated that recognition structures in the sphere of paid work and in private spheres di...

  9. Studies of human vision recognition: some improvements

    Science.gov (United States)

    Wu, Bo-Wen; Fang, Yi-Chin; Chang, Lin-Song

    2010-01-01

    This paper proposes a new method to improve human recognition by artificial intelligence, specifically of images without the interference of high frequencies. The human eye is the most delicate optical system. Notwithstanding the dramatic progression of its structure and functions through a long evolution, the capability of visual recognition is not yet close to perfection. This paper is a study, based on the limitations of recognition by the human eye, of image recognition through the application of artificial intelligence. Those aspects which have been explored focus on human eye modeling, including aberration analysis, creative models of the human eye, human vision recognition characteristics and various mathematical models for verification. By using images consisting of four black and white bands and modulation transfer function (MTF) curve evaluation recognition capability on all the studied models, the optimum model most compatible with the physiology of the human eye is found.

  10. The political transnationalism of Colombian migrants in New York and New Jersey (1990- 2010: Its understanding from the optics of identity wounds and the search for recognition

    Directory of Open Access Journals (Sweden)

    Constanza Amézquita Quintana

    2015-06-01

    Full Text Available This article aims to understand the dynamics of the political transnationalism of Colombian migrants in New York City and the northern area of New Jersey during the 1990-2010 period from the processes of contempt and moral suffering (social stigmatization, the implications of these processes in the migrants’ identity/autonomy (as generators of identity wounds and their search for social recognition. The paper begins with a characterization of the Colombian migration to that setting. Then it shows the experiences of moral contempt faced by Colombian migrants in the contexts of origin and arrival. In the context of origin such experiences were linked to social and political polarization, violence, inequality and strong barriers to upward mobility, while in the context of arrival these experiences were related to the stigma of drug trafficking, the dynamics of cultural racism, discrimination because of low English proficiency, and the absence of a legal immigration status. Finally, the article discusses the participation and mobilization (mainly at informal and collective levels of Colombian migrants in relation to the search for social recognition.

  11. The Neural Correlates of the Interaction between Semantic and Phonological Processing for Chinese Character Reading

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    Wang, Xiaojuan; Zhao, Rong; Zevin, Jason D.; Yang, Jianfeng

    2016-01-01

    Visual word recognition involves mappings among orthographic, phonological, and semantic codes. In alphabetic languages, it is hard to disentangle the effects of these codes, because orthographically well-formed words are typically pronounceable, confounding orthographic and phonological processes, and orthographic cues to meaning are rare, and where they occur are morphological, confounding orthographic and semantic processes. In Chinese character recognition, it is possible to explore orthography to phonology (O-P) and orthography to semantics (O-S) processes independently by taking advantage of the distinct phonetic and semantic components in Chinese phonograms. We analyzed data from an fMRI experiment using lexical decision for Chinese characters to explore the sensitivity of areas associated with character recognition to orthographic, phonological, and semantic processing. First, a correlation approach was used to identify regions associated with reaction time, frequency, consistency and visual complexity. Then, these ROIs were examined for their responses to stimuli with different types of information available. These results revealed two neural pathways, one for O-S processing relying on left middle temporal gyrus and angular gyrus, and the other for O-P processing relying on inferior frontal gyrus and insula. The two neural routes form a shared neural network both for real and pseudo-characters, and their cooperative division of labor reflects the neural basis for processing different types of characters. Results are broadly consistent with findings from alphabetic languages, as predicted by reading models that assume the same general architecture for logographic and alphabetic scripts. PMID:27445914

  12. Effects on Learning Logographic Character Formation in Computer-Assisted Handwriting Instruction

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    Tsai, Chen-hui; Kuo, Chin-Hwa; Horng, Wen-Bing; Chen, Chun-Wen

    2012-01-01

    This paper reports on a study that investigates how different learning methods might affect the learning process of character handwriting among beginning college learners of Chinese, as measured by tests of recognition, approximate production, precise production, and awareness of conventional stroke sequence. Two methodologies were examined during…

  13. The Inversion Effect for Chinese Characters Is Modulated by Radical Organization

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    Luo, Canhuang; Chen, Wei; Zhang, Ye

    2017-01-01

    In studies of visual object recognition, strong inversion effects accompany the acquisition of expertise and imply the involvement of configural processing. Chinese literacy results in sensitivity to the orthography of Chinese characters. While there is some evidence that this orthographic sensitivity results in an inversion effect, and thus…

  14. SKIN DETECTION OF ANIMATION CHARACTERS

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    Kazi Tanvir Ahmed Siddiqui

    2015-02-01

    Full Text Available The increasing popularity of animes makes it vulnerable to unwanted usages like copyright violations and pornography. That’s why, we need to develop a method to detect and recognize animation characters. Skin detection is one of the most important steps in this way. Though there are some methods to detect human skin color, but those methods do not work properly for anime characters. Anime skin varies greatly from human skin in color, texture, tone and in different kinds of lighting. They also vary greatly among themselves. Moreover, many other things (for example leather, shirt, hair etc., which are not skin, can have color similar to skin. In this paper, we have proposed three methods that can identify an anime character’s skin more successfully as compared with Kovac, Swift, Saleh and Osman methods, which are primarily designed for human skin detection. Our methods are based on RGB values and their comparative relations.

  15. Improved Offline Connected Script Recognition Based on Hybrid Strategy

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    Tanzila Saba

    2010-06-01

    Full Text Available In domain of analytic cursive word recognition, there are two main approaches: explicit segmentation based and implicit segmentation based. However, both approaches have their own shortcomings. To overcome individual weaknesses, this paper presents a hybrid strategy for recognition of strings of characters (words or numerals. In a two stage dynamic programming based, lexicon driven approach, first an explicit segmentation is applied to segment either cursive andwritten words or numeric strings. However, at this stage, segmentation points are not finalized. In the second verification stage, statistical features are extracted from each segmented area to recognize characters using a trained neural network. To enhance segmentation and recognition accuracy, lexicon is consulted using existing dynamic programming matching techniques. Accordingly, segmentation points are altered to decide true character boundaries byusing lexicon feedback. A rigorous experimental protocol shows high performance of the proposed method for cursive handwritten words and numeral strings.

  16. Character virtues in psychiatric practice.

    Science.gov (United States)

    Radden, Jennifer; Sadler, John Z

    2008-01-01

    The character-focused approach known as virtue ethics is especially well suited to understanding and promoting ethical psychiatric practice. Virtues are stable dispositions and responses attributed to character, and a virtue-based ethics is one in which people's selves or characters are at the center of moral assessment. In this discussion by a clinician and a philosopher, clinical scenarios using exchanges and inner monologue illustrate key aspects of virtues. Virtues are acquired through habituation; they are habits of mind as much as behavior; they are as a group heterogeneous, and individually composite; they involve affective responses; they are not impartial; they are compatible with the "role morality" required of professionals; they are responses to particular temptations and weaknesses; and they include, in the capacity for practical judgment known as phronesis, a way of resolving many of the conflicts and dilemmas that arise in practice. The virtue approach to ethics will likely be most useful in the educational setting where practitioners are learning clinical skills and socialized into the broad ethos of professional practice. Aspects of this educational effort are briefly reviewed, including whether it ought to be undertaken at all, whether the effort to teach virtues is possible, and, if so, how it can be achieved.

  17. Knowledge based recognition of harbor target

    Institute of Scientific and Technical Information of China (English)

    Zhu Bing; Li Jinzong; Cheng Aijun

    2006-01-01

    A fast knowledge based recognition method of the harbor target in large gray remote-sensing image is presented. First, the distributed features and the inherent feature are analyzed according to the knowledge of harbor targets; then, two methods for extracting the candidate region of harbor are devised in accordance with different sizes of the harbors; after that, thresholds are used to segment the land and the sea with strategies of the segmentation error control; finally, harbor recognition is implemented according to its inherent character (semi-closed region of seawater).

  18. Generalized Hidden Markov Models To Handwritten Devanagari Word Recognition

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    Mr. Pradeep Singh Thakur

    2012-06-01

    Full Text Available Hidden Markov Models (HMM have long been a popular choice for Western cursive handwriting recognition following their success in speech recognition. Even for the recognition of Oriental scripts such as Chinese, Japanese and Korean, Hidden Markov Models are increasingly being used to model substrokes of characters. However, when it comes to Indic script recognition, the published work employing HMMs is limited, and generally focused on isolated character recognition. In this effort, a data-driven HMM-based handwritten word recognition system for Hindi, an Indic script, is proposed. Though Devanagari is the script for Hindi, which is the official language of India, its character and word recognition pose great challenges due to large variety of symbols and their proximity in appearance. The accuracies obtained ranged from 30�0to 60�0with lexicon. These initial results are promising and warrant further research in this direction. The results are also encouraging to explore possibilities for adopting the approach to other Indic scripts as well.

  19. Automatic Vehicle License Recognition Based on Video Vehicular Detection System

    Institute of Scientific and Technical Information of China (English)

    YANG Zhaoxuan; CHEN Yang; HE Yinghua; WU Jun

    2006-01-01

    Traditional methods of license character extraction cannot meet the requirements of recognition accuracy and speed rendered by the video vehicular detection system.Therefore, a license plate localization method based on multi-scale edge detection and a character segmentation algorithm based on Markov random field model is presented.Results of experiments demonstrate that the method yields more accurate license character extraction in contrast to traditional localization method based on edge detection by difference operator and character segmentation based on threshold.The accuracy increases from 90% to 94% under preferable illumination, while under poor condition, it increases more than 5%.When the two improved algorithms are used, the accuracy and speed of automatic license recognition meet the system's requirement even under the noisy circumstance or uneven illumination.

  20. Fish Recognition Based on Robust Features Extraction from Size and Shape Measurements Using Neural Network

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    Mutasem K. Alsmadi

    2010-01-01

    Full Text Available Problem statement: Image recognition is a challenging problem researchers had been research into this area for so long especially in the recent years, due to distortion, noise, segmentation errors, overlap and occlusion of objects in digital images. In our study, there are many fields concern with pattern recognition, for example, fingerprint verification, face recognition, iris discrimination, chromosome shape discrimination, optical character recognition, texture discrimination and speech recognition, the subject of pattern recognition appears. A system for recognizing isolated pattern of interest may be as an approach for dealing with such application. Scientists and engineers with interests in image processing and pattern recognition have developed various approaches to deal with digital image recognition problems such as, neural network, contour matching and statistics. Approach: In this study, our aim was to recognize an isolated pattern of interest in the image based on the combination between robust features extraction. Where depend on size and shape measurements, that were extracted by measuring the distance and geometrical measurements. Results: We presented a system prototype for dealing with such problem. The system started by acquiring an image containing pattern of fish, then the image features extraction is performed relying on size and shape measurements. Our system has been applied on 20 different fish families, each family has a different number of fish types and our sample consists of distinct 350 of fish images. These images were divided into two datasets: 257 training images and 93 testing images. An overall accuracy was obtained using the neural network associated with the back-propagation algorithm was 86% on the test dataset used. Conclusion: We developed a classifier for fish images recognition. We efficiently have chosen a features extraction method to fit our demands. Our classifier successfully design and implement a