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.

Computerized literature reference system: use of an optical scanner and optical character recognition software.

Science.gov (United States)

Lossef, S V; Schwartz, L H

1990-09-01

A computerized reference system for radiology journal articles was developed by using an IBM-compatible personal computer with a hand-held optical scanner and optical character recognition software. This allows direct entry of scanned text from printed material into word processing or data-base files. Additionally, line diagrams and photographs of radiographs can be incorporated into these files. A text search and retrieval software program enables rapid searching for keywords in scanned documents. The hand scanner and software programs are commercially available, relatively inexpensive, and easily used. This permits construction of a personalized radiology literature file of readily accessible text and images requiring minimal typing or keystroke entry.

A New Experiment on Bengali Character Recognition

Science.gov (United States)

Barman, Sumana; Bhattacharyya, Debnath; Jeon, Seung-Whan; Kim, Tai-Hoon; Kim, Haeng-Kon

This paper presents a method to use View based approach in Bangla Optical Character Recognition (OCR) system providing reduced data set to the ANN classification engine rather than the traditional OCR methods. It describes how Bangla characters are processed, trained and then recognized with the use of a Backpropagation Artificial neural network. This is the first published account of using a segmentation-free optical character recognition system for Bangla using a view based approach. The methodology presented here assumes that the OCR pre-processor has presented the input images to the classification engine described here. The size and the font face used to render the characters are also significant in both training and classification. The images are first converted into greyscale and then to binary images; these images are then scaled to a fit a pre-determined area with a fixed but significant number of pixels. The feature vectors are then formed extracting the characteristics points, which in this case is simply a series of 0s and 1s of fixed length. Finally, an artificial neural network is chosen for the training and classification process.

Glyph Identification and Character Recognition for Sindhi OCR

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NISAR AHMEDMEMON

2017-10-01

Full Text Available A computer can read and write multiple languages and today?s computers are capable of understanding various human languages. A computer can be given instructions through various input methods but OCR (Optical Character Recognition and handwritten character recognition are the input methods in which a scanned page containing text is converted into written or editable text. The change in language text available on scanned page demands different algorithm to recognize text because every language and script pose varying number of challenges to recognize text. The Latin language recognition pose less difficulties compared to Arabic script and languages that use Arabic script for writing and OCR systems for these Latin languages are near to perfection. Very little work has been done on regional languages of Pakistan. In this paper the Sindhi glyphs are identified and the number of characters and connected components are identified for this regional language of Pakistan. A graphical user interface has been created to perform identification task for glyphs and characters of Sindhi language. The glyphs of characters are successfully identified from scanned page and this information can be used to recognize characters. The language glyph identification can be used to apply suitable algorithm to identify language as well as to achieve a higher recognition rate.

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.

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.

An analog VLSI real time optical character recognition system based on a neural architecture

International Nuclear Information System (INIS)

Bo, G.; Caviglia, D.; Valle, M.

1999-01-01

In this paper a real time Optical Character Recognition system is presented: it is based on a feature extraction module and a neural network classifier which have been designed and fabricated in analog VLSI technology. Experimental results validate the circuit functionality. The results obtained from a validation based on a mixed approach (i.e., an approach based on both experimental and simulation results) confirm the soundness and reliability of the system

An analog VLSI real time optical character recognition system based on a neural architecture

Energy Technology Data Exchange (ETDEWEB)

Bo, G.; Caviglia, D.; Valle, M. [Genoa Univ. (Italy). Dip. of Biophysical and Electronic Engineering

1999-03-01

In this paper a real time Optical Character Recognition system is presented: it is based on a feature extraction module and a neural network classifier which have been designed and fabricated in analog VLSI technology. Experimental results validate the circuit functionality. The results obtained from a validation based on a mixed approach (i.e., an approach based on both experimental and simulation results) confirm the soundness and reliability of the system.

Handwritten Sindhi Character Recognition Using Neural Networks

Directory of Open Access Journals (Sweden)

Shafique Ahmed Awan

2018-01-01

Full Text Available OCR (OpticalCharacter Recognition is a technology in which text image is used to understand and write text by machines. The work on languages containing isolated characters such as German, English, French and others is at its peak. The OCR and ICR (Intelligent Character Recognition research in Sindhi script is currently at in starting stages and not sufficient work have been cited in this area even though Sindhi language is rich in culture and history. This paper presents one of the initial steps in recognizing Sindhi handwritten characters. The isolated characters of Sindhi script written by thesubjects have been recognized. The various subjects were asked to write Sindhi characters in unconstrained form and then the written samples were collected and scanned through a flatbed scanner. The scanned documents were preprocessedwith the help of binary conversion, removing noise by pepper noise and the lines were segmented with the help of horizontal profile technique. The segmented lines were used to extract characters from scanned pages.This character segmentation was done by vertical projection. The extracted characters have been used to extract features so that the characters can be classified easily. Zoning was used for the feature extraction technique. For the classification, neural network has been used. The recognized characters converted into editable text with an average accuracy of 85%.

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.

The Compensatory Effectiveness of Optical Character Recognition/Speech Synthesis on Reading Comprehension of Postsecondary Students with Learning Disabilities.

Science.gov (United States)

Higgins, Eleanor L.; Raskind, Marshall H.

1997-01-01

Thirty-seven college students with learning disabilities were given a reading comprehension task under the following conditions: (1) using an optical character recognition/speech synthesis system; (2) having the text read aloud by a human reader; or (3) reading silently without assistance. Findings indicated that the greater the disability, the…

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.

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

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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.

Digitization of Full-Text Documents Before Publishing on the Internet: A Case Study Reviewing the Latest Optical Character Recognition Technologies.

Science.gov (United States)

McClean, Clare M.

1998-01-01

Reviews strengths and weaknesses of five optical character recognition (OCR) software packages used to digitize paper documents before publishing on the Internet. Outlines options available and stages of the conversion process. Describes the learning experience of Eurotext, a United Kingdom-based electronic libraries project (eLib). (PEN)

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.

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.

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.

Character Recognition Using Genetically Trained Neural Networks

Energy Technology Data Exchange (ETDEWEB)

Diniz, C.; Stantz, K.M.; Trahan, M.W.; Wagner, J.S.

1998-10-01

Computationally intelligent recognition of characters and symbols addresses a wide range of applications including foreign language translation and chemical formula identification. The combination of intelligent learning and optimization algorithms with layered neural structures offers powerful techniques for character recognition. These techniques were originally developed by Sandia National Laboratories for pattern and spectral analysis; however, their ability to optimize vast amounts of data make them ideal for character recognition. An adaptation of the Neural Network Designer soflsvare allows the user to create a neural network (NN_) trained by a genetic algorithm (GA) that correctly identifies multiple distinct characters. The initial successfid recognition of standard capital letters can be expanded to include chemical and mathematical symbols and alphabets of foreign languages, especially Arabic and Chinese. The FIN model constructed for this project uses a three layer feed-forward architecture. To facilitate the input of characters and symbols, a graphic user interface (GUI) has been developed to convert the traditional representation of each character or symbol to a bitmap. The 8 x 8 bitmap representations used for these tests are mapped onto the input nodes of the feed-forward neural network (FFNN) in a one-to-one correspondence. The input nodes feed forward into a hidden layer, and the hidden layer feeds into five output nodes correlated to possible character outcomes. During the training period the GA optimizes the weights of the NN until it can successfully recognize distinct characters. Systematic deviations from the base design test the network's range of applicability. Increasing capacity, the number of letters to be recognized, requires a nonlinear increase in the number of hidden layer neurodes. Optimal character recognition performance necessitates a minimum threshold for the number of cases when genetically training the net. And, the

A modern optical character recognition system in a real world clinical setting: some accuracy and feasibility observations.

Science.gov (United States)

Biondich, Paul G; Overhage, J Marc; Dexter, Paul R; Downs, Stephen M; Lemmon, Larry; McDonald, Clement J

2002-01-01

Advances in optical character recognition (OCR) software and computer hardware have stimulated a reevaluation of the technology and its ability to capture structured clinical data from preexisting paper forms. In our pilot evaluation, we measured the accuracy and feasibility of capturing vitals data from a pediatric encounter form that has been in use for over twenty years. We found that the software had a digit recognition rate of 92.4% (95% confidence interval: 91.6 to 93.2) overall. More importantly, this system was approximately three times as fast as our existing method of data entry. These preliminary results suggest that with further refinements in the approach and additional development, we may be able to incorporate OCR as another method for capturing structured clinical data.

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…

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.

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%.

Optical character recognition: an illustrated guide to the frontier

Science.gov (United States)

Nagy, George; Nartker, Thomas A.; Rice, Stephen V.

1999-12-01

We offer a perspective on the performance of current OCR systems by illustrating and explaining actual OCR errors made by three commercial devices. After discussing briefly the character recognition abilities of humans and computers, we present illustrated examples of recognition errors. The top level of our taxonomy of the causes of errors consists of Imaging Defects, Similar Symbols, Punctuation, and Typography. The analysis of a series of 'snippets' from this perspective provides insight into the strengths and weaknesses of current systems, and perhaps a road map to future progress. The examples were drawn from the large-scale tests conducted by the authors at the Information Science Research Institute of the University of Nevada, Las Vegas. By way of conclusion, we point to possible approaches for improving the accuracy of today's systems. The talk is based on our eponymous monograph, recently published in The Kluwer International Series in Engineering and Computer Science, Kluwer Academic Publishers, 1999.

Automated Degradation Diagnosis in Character Recognition System Subject to Camera Vibration

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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.

Chinese character recognition based on Gabor feature extraction and CNN

Science.gov (United States)

Xiong, Yudian; Lu, Tongwei; Jiang, Yongyuan

2018-03-01

As an important application in the field of text line recognition and office automation, Chinese character recognition has become an important subject of pattern recognition. However, due to the large number of Chinese characters and the complexity of its structure, there is a great difficulty in the Chinese character recognition. In order to solve this problem, this paper proposes a method of printed Chinese character recognition based on Gabor feature extraction and Convolution Neural Network(CNN). The main steps are preprocessing, feature extraction, training classification. First, the gray-scale Chinese character image is binarized and normalized to reduce the redundancy of the image data. Second, each image is convoluted with Gabor filter with different orientations, and the feature map of the eight orientations of Chinese characters is extracted. Third, the feature map through Gabor filters and the original image are convoluted with learning kernels, and the results of the convolution is the input of pooling layer. Finally, the feature vector is used to classify and recognition. In addition, the generalization capacity of the network is improved by Dropout technology. The experimental results show that this method can effectively extract the characteristics of Chinese characters and recognize Chinese characters.

Character context: a shape descriptor for Arabic handwriting recognition

Science.gov (United States)

Mudhsh, Mohammed; Almodfer, Rolla; Duan, Pengfei; Xiong, Shengwu

2017-11-01

In the handwriting recognition field, designing good descriptors are substantial to obtain rich information of the data. However, the handwriting recognition research of a good descriptor is still an open issue due to unlimited variation in human handwriting. We introduce a "character context descriptor" that efficiently dealt with the structural characteristics of Arabic handwritten characters. First, the character image is smoothed and normalized, then the character context descriptor of 32 feature bins is built based on the proposed "distance function." Finally, a multilayer perceptron with regularization is used as a classifier. On experimentation with a handwritten Arabic characters database, the proposed method achieved a state-of-the-art performance with recognition rate equal to 98.93% and 99.06% for the 66 and 24 classes, respectively.

Use of Splines in Handwritten Character Recognition

OpenAIRE

Sunil Kumar; Gopinath S,; Satish Kumar; Rajesh Chhikara

2010-01-01

Handwritten Character Recognition is software used to identify the handwritten characters and receive and interpret intelligible andwritten input from sources such as manuscript documents. The recent past several years has seen the development of many systems which are able to simulate the human brain actions. Among the many, the neural networks and the artificial intelligence are the most two important paradigms used. In this paper we propose a new algorithm for recognition of handwritten t...

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

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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

Braille Character Recognition Using Artificial Neural Network

OpenAIRE

Subur, Joko; Sardjono, Tri Arief; Mardiyanto, Ronny

2015-01-01

Braille letter is characters designed for the blind, consist of six embossed points, arranged in a standard braille character. Braille letters is touched and read using fingers, therefore the sensitivity of the fingers is important. Those characters need to be memorized, so it is very difficult to be learned. The aim of this research is to create a braille characters recognition system and translate it to alpha-numeric text. Webcam camera is used to capture braille image from braille characte...

Online recognition of Chinese characters: the state-of-the-art.

Science.gov (United States)

Liu, Cheng-Lin; Jaeger, Stefan; Nakagawa, Masaki

2004-02-01

Online handwriting recognition is gaining renewed interest owing to the increase of pen computing applications and new pen input devices. The recognition of Chinese characters is different from western handwriting recognition and poses a special challenge. To provide an overview of the technical status and inspire future research, this paper reviews the advances in online Chinese character recognition (OLCCR), with emphasis on the research works from the 1990s. Compared to the research in the 1980s, the research efforts in the 1990s aimed to further relax the constraints of handwriting, namely, the adherence to standard stroke orders and stroke numbers and the restriction of recognition to isolated characters only. The target of recognition has shifted from regular script to fluent script in order to better meet the requirements of practical applications. The research works are reviewed in terms of pattern representation, character classification, learning/adaptation, and contextual processing. We compare important results and discuss possible directions of future research.

Synthesis of Common Arabic Handwritings to Aid Optical Character Recognition Research

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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.

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.

reCAPTCHA: human-based character recognition via Web security measures.

Science.gov (United States)

von Ahn, Luis; Maurer, Benjamin; McMillen, Colin; Abraham, David; Blum, Manuel

2008-09-12

CAPTCHAs (Completely Automated Public Turing test to tell Computers and Humans Apart) are widespread security measures on the World Wide Web that prevent automated programs from abusing online services. They do so by asking humans to perform a task that computers cannot yet perform, such as deciphering distorted characters. Our research explored whether such human effort can be channeled into a useful purpose: helping to digitize old printed material by asking users to decipher scanned words from books that computerized optical character recognition failed to recognize. We showed that this method can transcribe text with a word accuracy exceeding 99%, matching the guarantee of professional human transcribers. Our apparatus is deployed in more than 40,000 Web sites and has transcribed over 440 million words.

Optical Pattern Recognition

Science.gov (United States)

Yu, Francis T. S.; Jutamulia, Suganda

2008-10-01

Contributors; Preface; 1. Pattern recognition with optics Francis T. S. Yu and Don A. Gregory; 2. Hybrid neural networks for nonlinear pattern recognition Taiwei Lu; 3. Wavelets, optics, and pattern recognition Yao Li and Yunglong Sheng; 4. Applications of the fractional Fourier transform to optical pattern recognition David Mendlovic, Zeev Zalesky and Haldum M. Oxaktas; 5. Optical implementation of mathematical morphology Tien-Hsin Chao; 6. Nonlinear optical correlators with improved discrimination capability for object location and recognition Leonid P. Yaroslavsky; 7. Distortion-invariant quadratic filters Gregory Gheen; 8. Composite filter synthesis as applied to pattern recognition Shizhou Yin and Guowen Lu; 9. Iterative procedures in electro-optical pattern recognition Joseph Shamir; 10. Optoelectronic hybrid system for three-dimensional object pattern recognition Guoguang Mu, Mingzhe Lu and Ying Sun; 11. Applications of photrefractive devices in optical pattern recognition Ziangyang Yang; 12. Optical pattern recognition with microlasers Eung-Gi Paek; 13. Optical properties and applications of bacteriorhodopsin Q. Wang Song and Yu-He Zhang; 14. Liquid-crystal spatial light modulators Aris Tanone and Suganda Jutamulia; 15. Representations of fully complex functions on real-time spatial light modulators Robert W. Cohn and Laurence G. Hassbrook; Index.

A novel handwritten character recognition system using gradient ...

Indian Academy of Sciences (India)

The issues faced by the handwritten character recognition systems are the similarity. ∗ ... tical/structural features have also been successfully used in character ..... The coordinates (xc, yc) of centroid are calculated by equations (4) and (5). xc =.

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.

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.

Common constraints limit Korean and English character recognition in peripheral vision.

Science.gov (United States)

He, Yingchen; Kwon, MiYoung; Legge, Gordon E

2018-01-01

The visual span refers to the number of adjacent characters that can be recognized in a single glance. It is viewed as a sensory bottleneck in reading for both normal and clinical populations. In peripheral vision, the visual span for English characters can be enlarged after training with a letter-recognition task. Here, we examined the transfer of training from Korean to English characters for a group of bilingual Korean native speakers. In the pre- and posttests, we measured visual spans for Korean characters and English letters. Training (1.5 hours × 4 days) consisted of repetitive visual-span measurements for Korean trigrams (strings of three characters). Our training enlarged the visual spans for Korean single characters and trigrams, and the benefit transferred to untrained English symbols. The improvement was largely due to a reduction of within-character and between-character crowding in Korean recognition, as well as between-letter crowding in English recognition. We also found a negative correlation between the size of the visual span and the average pattern complexity of the symbol set. Together, our results showed that the visual span is limited by common sensory (crowding) and physical (pattern complexity) factors regardless of the language script, providing evidence that the visual span reflects a universal bottleneck for text recognition.

The nuclear fuel rod character recognition system based on neural network technique

International Nuclear Information System (INIS)

Kim, Woong-Ki; Park, Soon-Yong; Lee, Yong-Bum; Kim, Seung-Ho; Lee, Jong-Min; Chien, Sung-Il.

1994-01-01

The nuclear fuel rods should be discriminated and managed systematically by numeric characters which are printed at the end part of each rod in the process of producing fuel assembly. The characters are used to examine manufacturing process of the fuel rods in the inspection process of irradiated fuel rod. Therefore automatic character recognition is one of the most important technologies to establish automatic manufacturing process of fuel assembly. In the developed character recognition system, mesh feature set extracted from each character written in the fuel rod is employed to train a neural network based on back-propagation algorithm as a classifier for character recognition system. Performance evaluation has been achieved on a test set which is not included in a training character set. (author)

IMAGE TYPE WATER METER CHARACTER RECOGNITION BASED ON EMBEDDED DSP

OpenAIRE

LIU Ying; HAN Yan-bin; ZHANG Yu-lin

2015-01-01

In the paper, we combined DSP processor with image processing algorithm and studied the method of water meter character recognition. We collected water meter image through camera at a fixed angle, and the projection method is used to recognize those digital images. The experiment results show that the method can recognize the meter characters accurately and artificial meter reading is replaced by automatic digital recognition, which improves working efficiency.

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.

Recognition of online handwritten Gurmukhi characters based on ...

Indian Academy of Sciences (India)

Karun Verma

as the recognition of characters using rule based post-pro- cessing algorithm. ... ods in their work in order to recognize handwriting with pen-based devices. ..... Centernew is the average y-coordinate value of new stroke and denotes the center ...

Optical Character Recognition Using Active Contour Segmentation

Directory of Open Access Journals (Sweden)

Nabeel Oudah

2018-01-01

Full Text Available Document analysis of images snapped by camera is a growing challenge. These photos are often poor-quality compound images, composed of various objects and text; this makes automatic analysis complicated. OCR is one of the image processing techniques which is used to perform automatic identification of texts. Existing image processing techniques need to manage many parameters in order to clearly recognize the text in such pictures. Segmentation is regarded one of these essential parameters. This paper discusses the accuracy of segmentation process and its effect over the recognition process. According to the proposed method, the images were firstly filtered using the wiener filter then the active contour algorithm could be applied in the segmentation process. The Tesseract OCR Engine was selected in order to evaluate the performance and identification accuracy of the proposed method. The results showed that a more accurate segmentation process shall lead to a more accurate recognition results. The rate of recognition accuracy was 0.95 for the proposed algorithm compared with 0.85 for the Tesseract OCR Engine.

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.

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.

Character recognition from trajectory by recurrent spiking neural networks.

Science.gov (United States)

Jiangrong Shen; Kang Lin; Yueming Wang; Gang Pan

2017-07-01

Spiking neural networks are biologically plausible and power-efficient on neuromorphic hardware, while recurrent neural networks have been proven to be efficient on time series data. However, how to use the recurrent property to improve the performance of spiking neural networks is still a problem. This paper proposes a recurrent spiking neural network for character recognition using trajectories. In the network, a new encoding method is designed, in which varying time ranges of input streams are used in different recurrent layers. This is able to improve the generalization ability of our model compared with general encoding methods. The experiments are conducted on four groups of the character data set from University of Edinburgh. The results show that our method can achieve a higher average recognition accuracy than existing methods.

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.

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 usability evaluation of an interactive application for halal products using optical character recognition and augmented reality technologies

Science.gov (United States)

Lam, Meng Chun; Nizam, Siti Soleha Muhammad; Arshad, Haslina; A'isyah Ahmad Shukri, Saidatul; Hashim, Nurhazarifah Che; Putra, Haekal Mozzia; Abidin, Rimaniza Zainal

2017-10-01

This article discusses the usability of an interactive application for halal products using Optical Character Recognition (OCR) and Augmented Reality (AR) technologies. Among the problems that have been identified in this study is that consumers have little knowledge about the E-Code. Therefore, users often have doubts about the halal status of the product. Nowadays, the integrity of halal status can be doubtful due to the actions of some irresponsible people spreading false information about a product. Therefore, an application that uses OCR and AR technology developed in this study will help the users to identify the information content of a product by scanning the E-Code label and by scanning the product's brand to know the halal status of the product. In this application, E-Code on the label of a product is scanned using OCR technology to display information about the E-Code. The product's brand is scan using augmented reality technology to display halal status of the product. The findings reveal that users are satisfied with this application and it is useful and easy to use.

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.

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.

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

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.

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

International Nuclear Information System (INIS)

Cho, Jai Wan; Jeong, Kyung Min

2012-01-01

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

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

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

Directory of Open Access Journals (Sweden)

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.

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

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.

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

Two-stage neural-network-based technique for Urdu character two-dimensional shape representation, classification, and recognition

Science.gov (United States)

Megherbi, Dalila B.; Lodhi, S. M.; Boulenouar, A. J.

2001-03-01

This work is in the field of automated document processing. This work addresses the problem of representation and recognition of Urdu characters using Fourier representation and a Neural Network architecture. In particular, we show that a two-stage Neural Network scheme is used here to make classification of 36 Urdu characters into seven sub-classes namely subclasses characterized by seven proposed and defined fuzzy features specifically related to Urdu characters. We show that here Fourier Descriptors and Neural Network provide a remarkably simple way to draw definite conclusions from vague, ambiguous, noisy or imprecise information. In particular, we illustrate the concept of interest regions and describe a framing method that provides a way to make the proposed technique for Urdu characters recognition robust and invariant to scaling and translation. We also show that a given character rotation is dealt with by using the Hotelling transform. This transform is based upon the eigenvalue decomposition of the covariance matrix of an image, providing a method of determining the orientation of the major axis of an object within an image. Finally experimental results are presented to show the power and robustness of the proposed two-stage Neural Network based technique for Urdu character recognition, its fault tolerance, and high recognition accuracy.

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.

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

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.

2016-01-01

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…

Distorted Character Recognition Via An Associative Neural Network

Science.gov (United States)

Messner, Richard A.; Szu, Harold H.

1987-03-01

The purpose of this paper is two-fold. First, it is intended to provide some preliminary results of a character recognition scheme which has foundations in on-going neural network architecture modeling, and secondly, to apply some of the neural network results in a real application area where thirty years of effort has had little effect on providing the machine an ability to recognize distorted objects within the same object class. It is the author's belief that the time is ripe to start applying in ernest the results of over twenty years of effort in neural modeling to some of the more difficult problems which seem so hard to solve by conventional means. The character recognition scheme proposed utilizes a preprocessing stage which performs a 2-dimensional Walsh transform of an input cartesian image field, then sequency filters this spectrum into three feature bands. Various features are then extracted and organized into three sets of feature vectors. These vector patterns that are stored and recalled associatively. Two possible associative neural memory models are proposed for further investigation. The first being an outer-product linear matrix associative memory with a threshold function controlling the strength of the output pattern (similar to Kohonen's crosscorrelation approach [1]). The second approach is based upon a modified version of Grossberg's neural architecture [2] which provides better self-organizing properties due to its adaptive nature. Preliminary results of the sequency filtering and feature extraction preprocessing stage and discussion about the use of the proposed neural architectures is included.

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.

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%.

A simple and efficient optical character recognition system for basic ...

Indian Academy of Sciences (India)

are on the way for the development of efficient OCR systems for Indian languages, .... Each vowel has a vowel sign (modifier) and each consonant has a basic form (prim- itive). ..... as a single class of character in the first stage of classification.

Charactering lidar optical subsystem using four quadrants method

Science.gov (United States)

Tian, Xiaomin; Liu, Dong; Xu, Jiwei; Wang, Zhenzhu; Wang, Bangxin; Wu, Decheng; Zhong, Zhiqing; Xie, Chenbo; Wang, Yingjian

2018-02-01

Lidar is a kind of active optical remote sensing instruments , can be applied to sound atmosphere with a high spatial and temporal resolution. Many parameter of atmosphere can be get by using different inverse algorithm with lidar backscatter signal. The basic setup of a lidar consist of a transmitter and a receiver. To make sure the quality of lidar signal data, the lidar must be calibrated before being used to measure the atmospheric variables. It is really significant to character and analyze lidar optical subsystem because a well equiped lidar optical subsystem contributes to high quality lidar signal data. we pay close attention to telecover test to character and analyze lidar optical subsystem.The telecover test is called four quadrants method consisting in dividing the telescope aperture in four quarants. when a lidar is well configured with lidar optical subsystem, the normalized signal from four qudrants will agree with each other on some level. Testing our WARL-II lidar by four quadrants method ,we find the signals of the four basically consistent with each other both in near range and in far range. But in detail, the signals in near range have some slight distinctions resulting from overlap function, some signals distinctions are induced by atmospheric instability.

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.

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.

Liquid lens: advances in adaptive optics

Science.gov (United States)

Casey, Shawn Patrick

2010-12-01

'Liquid lens' technologies promise significant advancements in machine vision and optical communications systems. Adaptations for machine vision, human vision correction, and optical communications are used to exemplify the versatile nature of this technology. Utilization of liquid lens elements allows the cost effective implementation of optical velocity measurement. The project consists of a custom image processor, camera, and interface. The images are passed into customized pattern recognition and optical character recognition algorithms. A single camera would be used for both speed detection and object recognition.

Waveguide-type optical circuits for recognition of optical 8QAM-coded label

Science.gov (United States)

Surenkhorol, Tumendemberel; Kishikawa, Hiroki; Goto, Nobuo; Gonchigsumlaa, Khishigjargal

2017-10-01

Optical signal processing is expected to be applied in network nodes. In photonic routers, label recognition is one of the important functions. We have studied different kinds of label recognition methods so far for on-off keying, binary phase-shift keying, quadrature phase-shift keying, and 16 quadrature amplitude modulation-coded labels. We propose a method based on waveguide circuits to recognize an optical eight quadrature amplitude modulation (8QAM)-coded label by simple passive optical signal processing. The recognition of the proposed method is theoretically analyzed and numerically simulated by the finite difference beam propagation method. The noise tolerance is discussed, and bit-error rate against optical signal-to-noise ratio is evaluated. The scalability of the proposed method is also discussed theoretically for two-symbol length 8QAM-coded labels.

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.

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.

Automated target recognition and tracking using an optical pattern recognition neural network

Science.gov (United States)

Chao, Tien-Hsin

1991-01-01

The on-going development of an automatic target recognition and tracking system at the Jet Propulsion Laboratory is presented. This system is an optical pattern recognition neural network (OPRNN) that is an integration of an innovative optical parallel processor and a feature extraction based neural net training algorithm. The parallel optical processor provides high speed and vast parallelism as well as full shift invariance. The neural network algorithm enables simultaneous discrimination of multiple noisy targets in spite of their scales, rotations, perspectives, and various deformations. This fully developed OPRNN system can be effectively utilized for the automated spacecraft recognition and tracking that will lead to success in the Automated Rendezvous and Capture (AR&C) of the unmanned Cargo Transfer Vehicle (CTV). One of the most powerful optical parallel processors for automatic target recognition is the multichannel correlator. With the inherent advantages of parallel processing capability and shift invariance, multiple objects can be simultaneously recognized and tracked using this multichannel correlator. This target tracking capability can be greatly enhanced by utilizing a powerful feature extraction based neural network training algorithm such as the neocognitron. The OPRNN, currently under investigation at JPL, is constructed with an optical multichannel correlator where holographic filters have been prepared using the neocognitron training algorithm. The computation speed of the neocognitron-type OPRNN is up to 10(exp 14) analog connections/sec that enabling the OPRNN to outperform its state-of-the-art electronics counterpart by at least two orders of magnitude.

Automatic feature design for optical character recognition using an evolutionary search procedure.

Science.gov (United States)

Stentiford, F W

1985-03-01

An automatic evolutionary search is applied to the problem of feature extraction in an OCR application. A performance measure based on feature independence is used to generate features which do not appear to suffer from peaking effects [17]. Features are extracted from a training set of 30 600 machine printed 34 class alphanumeric characters derived from British mail. Classification results on the training set and a test set of 10 200 characters are reported for an increasing number of features. A 1.01 percent forced decision error rate is obtained on the test data using 316 features. The hardware implementation should be cheap and fast to operate. The performance compares favorably with current low cost OCR page readers.

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.

Angular spectrum characters of high gain non-critical phase match optical parametric oscillators

International Nuclear Information System (INIS)

Liu Jian-Hui; Liu Qiang; Gong Ma-Li

2011-01-01

The angular spectrum gain characters and the power magnification characters of high gain non-walk-off colinear optical parametric oscillators have been studied using the non-colinear phase match method for the first time. The experimental results of the KTiOAsO 4 and the KTiOPO 4 crystals are discussed in detail. At the high energy single resonant condition, low reflective ratio of the output mirror for the signal and long non-linear crystal are beneficial for small divergence angles. This method can also be used for other high gain non-walk-off phase match optical parametric processes. (electromagnetism, optics, acoustics, heat transfer, classical mechanics, and fluid dynamics)

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

Javanese Character Feature Extraction Based on Shape Energy

Directory of Open Access Journals (Sweden)

Galih Hendra Wibowo

2017-07-01

Full Text Available Javanese character is one of Indonesia's noble culture, especially in Java. However, the number of Javanese people who are able to read the letter has decreased so that there need to be conservation efforts in the form of a system that is able to recognize the characters. One solution to these problem lies in Optical Character Recognition (OCR studies, where one of its heaviest points lies in feature extraction which is to distinguish each character. Shape Energy is one of feature extraction method with the basic idea of how the character can be distinguished simply through its skeleton. Based on the basic idea, then the development of feature extraction is done based on its components to produce an angular histogram with various variations of multiples angle. Furthermore, the performance test of this method and its basic method is performed in Javanese character dataset, which has been obtained from various images, is 240 data with 19 labels by using K-Nearest Neighbors as its classification method. Performance values were obtained based on the accuracy which is generated through the Cross-Validation process of 80.83% in the angular histogram with an angle of 20 degrees, 23% better than Shape Energy. In addition, other test results show that this method is able to recognize rotated character with the lowest performance value of 86% at 180-degree rotation and the highest performance value of 96.97% at 90-degree rotation. It can be concluded that this method is able to improve the performance of Shape Energy in the form of recognition of Javanese characters as well as robust to the rotation.

Analog design of a new neural network for optical character recognition.

Science.gov (United States)

Morns, I P; Dlay, S S

1999-01-01

An electronic circuit is presented for a new type of neural network, which gives a recognition rate of over 100 kHz. The network is used to classify handwritten numerals, presented as Fourier and wavelet descriptors, and has been shown to train far quicker than the popular backpropagation network while maintaining classification accuracy.

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.

Optical Pattern Recognition for Missile Guidance.

Science.gov (United States)

1982-11-15

directed to novel pattern recognition algo- rithms (that allow pattern recognition and object classification in the face of various geometrical and...I wats EF5 = 50) p.j/t’ni 2 (for btith image pat tern recognitio itas a preproicessing oiperatiton. Ini devices). TIhe rt’ad light intensity (0.33t mW...electrodes on its large faces . This Priz light modulator and the motivation for its devel- SLM is known as the Prom (Pockels real-time optical opment. In Sec

The DSFPN, a new neural network for optical character recognition.

Science.gov (United States)

Morns, L P; Dlay, S S

1999-01-01

A new type of neural network for recognition tasks is presented in this paper. The network, called the dynamic supervised forward-propagation network (DSFPN), is based on the forward only version of the counterpropagation network (CPN). The DSFPN, trains using a supervised algorithm and can grow dynamically during training, allowing subclasses in the training data to be learnt in an unsupervised manner. It is shown to train in times comparable to the CPN while giving better classification accuracies than the popular backpropagation network. Both Fourier descriptors and wavelet descriptors are used for image preprocessing and the wavelets are proven to give a far better performance.

Handwritten Devanagari Character Recognition Using Layer-Wise Training of Deep Convolutional Neural Networks and Adaptive Gradient Methods

Directory of Open Access Journals (Sweden)

Mahesh Jangid

2018-02-01

Full Text Available Handwritten character recognition is currently getting the attention of researchers because of possible applications in assisting technology for blind and visually impaired users, human–robot interaction, automatic data entry for business documents, etc. In this work, we propose a technique to recognize handwritten Devanagari characters using deep convolutional neural networks (DCNN which are one of the recent techniques adopted from the deep learning community. We experimented the ISIDCHAR database provided by (Information Sharing Index ISI, Kolkata and V2DMDCHAR database with six different architectures of DCNN to evaluate the performance and also investigate the use of six recently developed adaptive gradient methods. A layer-wise technique of DCNN has been employed that helped to achieve the highest recognition accuracy and also get a faster convergence rate. The results of layer-wise-trained DCNN are favorable in comparison with those achieved by a shallow technique of handcrafted features and standard DCNN.

Fringe patterns generated by micro-optical sensors for pattern recognition.

Science.gov (United States)

Tamee, Kreangsak; Chaiwong, Khomyuth; Yothapakdee, Kriengsak; Yupapin, Preecha P

2015-01-01

We present a new result of pattern recognition generation scheme using a small-scale optical muscle sensing system, which consisted of an optical add-drop filter incorporating two nonlinear optical side ring resonators. When light from laser source enters into the system, the device is stimulated by an external physical parameter that introduces a change in the phase of light propagation within the sensing device, which can be formed by the interference fringe patterns. Results obtained have shown that the fringe patterns can be used to form the relationship between signal patterns and fringe pattern recognitions.

Face recognition in securing optical telecom network equipment

International Nuclear Information System (INIS)

Ali, N.M.

2015-01-01

In this paper, face recognition is used with a microcontroller based hardware module to secure the telecommunication equipments like ONU (optical network units) or any other telecommunication equipment. The face recognition classifier value optimization adaption is deployed and in this scheme by increasing or decreasing the number of images in the database will automatically generate and adopt the classifier value for recognition of known and unknown persons. On recognizing and unknown persons. On recognizing an unknown person, the hardware module will send an SMS to the concerned security personnel for security preventive measures. (author)

Optical-electronic shape recognition system based on synergetic associative memory

Science.gov (United States)

Gao, Jun; Bao, Jie; Chen, Dingguo; Yang, Youqing; Yang, Xuedong

2001-04-01

This paper presents a novel optical-electronic shape recognition system based on synergetic associative memory. Our shape recognition system is composed of two parts: the first one is feature extraction system; the second is synergetic pattern recognition system. Hough transform is proposed for feature extraction of unrecognized object, with the effects of reducing dimensions and filtering for object distortion and noise, synergetic neural network is proposed for realizing associative memory in order to eliminate spurious states. Then we adopt an approach of optical- electronic realization to our system that can satisfy the demands of real time, high speed and parallelism. In order to realize fast algorithm, we replace the dynamic evolution circuit with adjudge circuit according to the relationship between attention parameters and order parameters, then implement the recognition of some simple images and its validity is proved.

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.

Examination of soldier target recognition with direct view optics

Science.gov (United States)

Long, Frederick H.; Larkin, Gabriella; Bisordi, Danielle; Dorsey, Shauna; Marianucci, Damien; Goss, Lashawnta; Bastawros, Michael; Misiuda, Paul; Rodgers, Glenn; Mazz, John P.

2017-10-01

Target recognition and identification is a problem of great military and scientific importance. To examine the correlation between target recognition and optical magnification, ten U.S. Army soldiers were tasked with identifying letters on targets at 800 and 1300 meters away. Letters were used since they are a standard method for measuring visual acuity. The letters were approximately 90 cm high, which is the size of a well-known rifle. Four direct view optics with angular magnifications of 1.5x, 4x, 6x, and 9x were used. The goal of this approach was to measure actual probabilities for correct target identification. Previous scientific literature suggests that target recognition can be modeled as a linear response problem in angular frequency space using the established values for the contrast sensitivity function for a healthy human eye and the experimentally measured modulation transfer function of the optic. At the 9x magnification, the soldiers could identify the letters with almost no errors (i.e., 97% probability of correct identification). At lower magnification, errors in letter identification were more frequent. The identification errors were not random but occurred most frequently with a few pairs of letters (e.g., O and Q), which is consistent with the literature for letter recognition. In addition, in the small subject sample of ten soldiers, there was considerable variation in the observer recognition capability at 1.5x and a range of 800 meters. This can be directly attributed to the variation in the observer visual acuity.

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.

Recognition characters and new records of two species of Phylloscyrtini (Orthoptera, Gryllidae, Trigonidiinae from southern Brazil

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Luciano de P. Martins

2012-03-01

Full Text Available The Phylloscyrtini occurs from eastern United States to Argentina and includes 21 valid species. It is a highly neglected group of crickets and little is known about its biology and distribution. Cranistus colliurides Stål, 1861 and Phylloscyrtus amoenus (Burmeister, 1880 were recorded for the state of Rio Grande do Sul, southern Brazil, and information on calling song, stridulatory file and recognition characters were provided.

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…

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...

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

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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.

New technique for number-plate recognition

Science.gov (United States)

Guo, Jie; Shi, Peng-Fei

2001-09-01

This paper presents an alternative algorithm for number plate recognition. The algorithm consists of three modules. Respectively, they are number plate location module, character segmentation module and character recognition module. Number plate location module extracts the number plate from the detected car image by analyzing the color and the texture properties. Different from most license plate location methods, the algorithm has fewer limits to the car size, the car position in the image and the image background. Character segmentation module applies connected region algorithm both to eliminate noise points and to segment characters. Touching characters and broken characters can be processed correctly. Character recognition module recognizes characters with HHIC (Hierarchical Hybrid Integrated Classifier). The system has been tested with 100 images obtained from crossroad and parking lot, etc, where the cars have different size, position, background and illumination. Successful recognition rate is about 92%. The average processing time is 1.2 second.

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

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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.

A DDC Bibliography on Optical or Graphic Information Processing (Information Sciences Series). Volume I.

Science.gov (United States)

Defense Documentation Center, Alexandria, VA.

This unclassified-unlimited bibliography contains 183 references, with abstracts, dealing specifically with optical or graphic information processing. Citations are grouped under three headings: display devices and theory, character recognition, and pattern recognition. Within each group, they are arranged in accession number (AD-number) sequence.…

When is the right hemisphere holistic and when is it not? The case of Chinese character recognition.

Science.gov (United States)

Chung, Harry K S; Leung, Jacklyn C Y; Wong, Vienne M Y; Hsiao, Janet H

2018-05-15

Holistic processing (HP) has long been considered a characteristic of right hemisphere (RH) processing. Indeed, holistic face processing is typically associated with left visual field (LVF)/RH processing advantages. Nevertheless, expert Chinese character recognition involves reduced HP and increased RH lateralization, presenting a counterexample. Recent modeling research suggests that RH processing may be associated with an increase or decrease in HP, depending on whether spacing or component information was used respectively. Since expert Chinese character recognition involves increasing sensitivity to components while deemphasizing spacing information, RH processing in experts may be associated with weaker HP than novices. Consistent with this hypothesis, in a divided visual field paradigm, novices exhibited HP only in the LVF/RH, whereas experts showed no HP in either visual field. This result suggests that the RH may flexibly switch between part-based and holistic representations, consistent with recent fMRI findings. The RH's advantage in global/low spatial frequency processing is suggested to be relative to the task relevant frequency range. Thus, its use of holistic and part-based representations may depend on how attention is allocated for task relevant information. This study provides the first behavioral evidence showing how type of information used for processing modulates perceptual representations in the RH. Copyright © 2018 Elsevier B.V. All rights reserved.

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.

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.

Printed Persian Subword Recognition Using Wavelet Packet Descriptors

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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.

Optical pattern recognition III; Proceedings of the Meeting, Orlando, FL, Apr. 21, 22, 1992

Science.gov (United States)

Casasent, David P. (Editor); Chao, Tien-Hsin (Editor)

1992-01-01

Consideration is given to transitioning of optical processing into systems (TOPS), optical correlator hardware, phase-only optical correlation filters, optical distortion-invariant correlation filters, and optical neural networks. Particular attention is given to a test target for optical correlators, a TOPS electronic warfare channelizer program, a portable video-rate optical correlator, a joint transform correlator employing electron trapping materials, a novelty filtered optical correlator using a photorefractive crystal, a comparison of correlation performance of smart ternary phase-amplitude filters with gray-scale and binary input scenes, real-time distortion-tolerant composite filters for automatic target identification, landscaping the correlation surface, fast designing of a circular harmonic filter using simulated annealing, feature-based correlation filters for distortion invariance, automatic target recognition using a feature-based optical neural network, and a holographic inner-product processor for pattern recognition.

Multi-font printed Mongolian document recognition system

Science.gov (United States)

Peng, Liangrui; Liu, Changsong; Ding, Xiaoqing; Wang, Hua; Jin, Jianming

2009-01-01

Mongolian is one of the major ethnic languages in China. Large amount of Mongolian printed documents need to be digitized in digital library and various applications. Traditional Mongolian script has unique writing style and multi-font-type variations, which bring challenges to Mongolian OCR research. As traditional Mongolian script has some characteristics, for example, one character may be part of another character, we define the character set for recognition according to the segmented components, and the components are combined into characters by rule-based post-processing module. For character recognition, a method based on visual directional feature and multi-level classifiers is presented. For character segmentation, a scheme is used to find the segmentation point by analyzing the properties of projection and connected components. As Mongolian has different font-types which are categorized into two major groups, the parameter of segmentation is adjusted for each group. A font-type classification method for the two font-type group is introduced. For recognition of Mongolian text mixed with Chinese and English, language identification and relevant character recognition kernels are integrated. Experiments show that the presented methods are effective. The text recognition rate is 96.9% on the test samples from practical documents with multi-font-types and mixed scripts.

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.

Handwritten recognition of Tamil vowels using deep learning

Science.gov (United States)

Ram Prashanth, N.; Siddarth, B.; Ganesh, Anirudh; Naveen Kumar, Vaegae

2017-11-01

We come across a large volume of handwritten texts in our daily lives and handwritten character recognition has long been an important area of research in pattern recognition. The complexity of the task varies among different languages and it so happens largely due to the similarity between characters, distinct shapes and number of characters which are all language-specific properties. There have been numerous works on character recognition of English alphabets and with laudable success, but regional languages have not been dealt with very frequently and with similar accuracies. In this paper, we explored the performance of Deep Belief Networks in the classification of Handwritten Tamil vowels, and conclusively compared the results obtained. The proposed method has shown satisfactory recognition accuracy in light of difficulties faced with regional languages such as similarity between characters and minute nuances that differentiate them. We can further extend this to all the Tamil characters.

Vehicle license plate recognition based on geometry restraints and multi-feature decision

Science.gov (United States)

Wu, Jianwei; Wang, Zongyue

2005-10-01

Vehicle license plate (VLP) recognition is of great importance to many traffic applications. Though researchers have paid much attention to VLP recognition there has not been a fully operational VLP recognition system yet for many reasons. This paper discusses a valid and practical method for vehicle license plate recognition based on geometry restraints and multi-feature decision including statistical and structural features. In general, the VLP recognition includes the following steps: the location of VLP, character segmentation, and character recognition. This paper discusses the three steps in detail. The characters of VLP are always declining caused by many factors, which makes it more difficult to recognize the characters of VLP, therefore geometry restraints such as the general ratio of length and width, the adjacent edges being perpendicular are used for incline correction. Image Moment has been proved to be invariant to translation, rotation and scaling therefore image moment is used as one feature for character recognition. Stroke is the basic element for writing and hence taking it as a feature is helpful to character recognition. Finally we take the image moment, the strokes and the numbers of each stroke for each character image and some other structural features and statistical features as the multi-feature to match each character image with sample character images so that each character image can be recognized by BP neural net. The proposed method combines statistical and structural features for VLP recognition, and the result shows its validity and efficiency.

Implementation theory of distortion-invariant pattern recognition for optical and digital signal processing systems

Science.gov (United States)

Lhamon, Michael Earl

A pattern recognition system which uses complex correlation filter banks requires proportionally more computational effort than single-real valued filters. This introduces increased computation burden but also introduces a higher level of parallelism, that common computing platforms fail to identify. As a result, we consider algorithm mapping to both optical and digital processors. For digital implementation, we develop computationally efficient pattern recognition algorithms, referred to as, vector inner product operators that require less computational effort than traditional fast Fourier methods. These algorithms do not need correlation and they map readily onto parallel digital architectures, which imply new architectures for optical processors. These filters exploit circulant-symmetric matrix structures of the training set data representing a variety of distortions. By using the same mathematical basis as with the vector inner product operations, we are able to extend the capabilities of more traditional correlation filtering to what we refer to as "Super Images". These "Super Images" are used to morphologically transform a complicated input scene into a predetermined dot pattern. The orientation of the dot pattern is related to the rotational distortion of the object of interest. The optical implementation of "Super Images" yields feature reduction necessary for using other techniques, such as artificial neural networks. We propose a parallel digital signal processor architecture based on specific pattern recognition algorithms but general enough to be applicable to other similar problems. Such an architecture is classified as a data flow architecture. Instead of mapping an algorithm to an architecture, we propose mapping the DSP architecture to a class of pattern recognition algorithms. Today's optical processing systems have difficulties implementing full complex filter structures. Typically, optical systems (like the 4f correlators) are limited to phase

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.

[Delays produced by prolonged viewing in the recognition of Kanji characters: analysis of the "Gestaltzerfall" phenomenon].

Science.gov (United States)

Ninose, Y; Gyoba, J

1996-08-01

It is a well-known observation that when a Kanji character is viewed steadily and continuously, the viewer often becomes unable to recognize the Kanji as a whole pattern and it becomes difficult to judge whether or not the Kanji is orthographically correct. Such a phenomenon is called the "Gestaltzerfall" of Kanji characters. In the present study, two experiments were carried out to examine delays in the recognition of test Kanji following 25 s of prolonged viewing of adaptation Kanji, which were comprised of either the same or different parts and structures. When the size of the adaptation Kanji was equal to that of the test Kanji, there were significant delays of more than 50 ms, both when the stimuli were of the same pattern, and when they had the same structure but different components. However, when their sizes were different, delays were found only when the test and the adaptation Kanji were of the same pattern. These results suggest that a Kanji pattern may be internally represented as a whole, independent of its size, while the processing of Kanji structure may be dependent upon its size. Prolonged viewing may produce an adaptation effect specific to such representations.

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...

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%.

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.

Drawing and Recognizing Chinese Characters with Recurrent Neural Network.

Science.gov (United States)

Zhang, Xu-Yao; Yin, Fei; Zhang, Yan-Ming; Liu, Cheng-Lin; Bengio, Yoshua

2018-04-01

Recent deep learning based approaches have achieved great success on handwriting recognition. Chinese characters are among the most widely adopted writing systems in the world. Previous research has mainly focused on recognizing handwritten Chinese characters. However, recognition is only one aspect for understanding a language, another challenging and interesting task is to teach a machine to automatically write (pictographic) Chinese characters. In this paper, we propose a framework by using the recurrent neural network (RNN) as both a discriminative model for recognizing Chinese characters and a generative model for drawing (generating) Chinese characters. To recognize Chinese characters, previous methods usually adopt the convolutional neural network (CNN) models which require transforming the online handwriting trajectory into image-like representations. Instead, our RNN based approach is an end-to-end system which directly deals with the sequential structure and does not require any domain-specific knowledge. With the RNN system (combining an LSTM and GRU), state-of-the-art performance can be achieved on the ICDAR-2013 competition database. Furthermore, under the RNN framework, a conditional generative model with character embedding is proposed for automatically drawing recognizable Chinese characters. The generated characters (in vector format) are human-readable and also can be recognized by the discriminative RNN model with high accuracy. Experimental results verify the effectiveness of using RNNs as both generative and discriminative models for the tasks of drawing and recognizing Chinese characters.

Word-level recognition of multifont Arabic text using a feature vector matching approach

Science.gov (United States)

Erlandson, Erik J.; Trenkle, John M.; Vogt, Robert C., III

1996-03-01

Many text recognition systems recognize text imagery at the character level and assemble words from the recognized characters. An alternative approach is to recognize text imagery at the word level, without analyzing individual characters. This approach avoids the problem of individual character segmentation, and can overcome local errors in character recognition. A word-level recognition system for machine-printed Arabic text has been implemented. Arabic is a script language, and is therefore difficult to segment at the character level. Character segmentation has been avoided by recognizing text imagery of complete words. The Arabic recognition system computes a vector of image-morphological features on a query word image. This vector is matched against a precomputed database of vectors from a lexicon of Arabic words. Vectors from the database with the highest match score are returned as hypotheses for the unknown image. Several feature vectors may be stored for each word in the database. Database feature vectors generated using multiple fonts and noise models allow the system to be tuned to its input stream. Used in conjunction with database pruning techniques, this Arabic recognition system has obtained promising word recognition rates on low-quality multifont text imagery.

Digital and optical shape representation and pattern recognition; Proceedings of the Meeting, Orlando, FL, Apr. 4-6, 1988

Science.gov (United States)

Juday, Richard D. (Editor)

1988-01-01

The present conference discusses topics in pattern-recognition correlator architectures, digital stereo systems, geometric image transformations and their applications, topics in pattern recognition, filter algorithms, object detection and classification, shape representation techniques, and model-based object recognition methods. Attention is given to edge-enhancement preprocessing using liquid crystal TVs, massively-parallel optical data base management, three-dimensional sensing with polar exponential sensor arrays, the optical processing of imaging spectrometer data, hybrid associative memories and metric data models, the representation of shape primitives in neural networks, and the Monte Carlo estimation of moment invariants for pattern recognition.

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

2016-03-01

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. 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 but do not assume phonological processing being LH lateralized, we show that 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. This effect is due to higher visual similarity among characters in the dominant type than the minority type, demonstrating the modulation of visual similarity of words on hemispheric lateralization. Copyright © 2015 Cognitive Science Society, Inc.

Modified-hybrid optical neural network filter for multiple object recognition within cluttered scenes

Science.gov (United States)

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

2009-08-01

Motivated by the non-linear interpolation and generalization abilities of the hybrid optical neural network filter between the reference and non-reference images of the true-class object we designed the modifiedhybrid optical neural network filter. We applied an optical mask to the hybrid optical neural network's filter input. The mask was built with the constant weight connections of a randomly chosen image included in the training set. The resulted design of the modified-hybrid optical neural network filter is optimized for performing best in cluttered scenes of the true-class object. Due to the shift invariance properties inherited by its correlator unit the filter can accommodate multiple objects of the same class to be detected within an input cluttered image. Additionally, the architecture of the neural network unit of the general hybrid optical neural network filter allows the recognition of multiple objects of different classes within the input cluttered image by modifying the output layer of the unit. We test the modified-hybrid optical neural network filter for multiple objects of the same and of different classes' recognition within cluttered input images and video sequences of cluttered scenes. The filter is shown to exhibit with a single pass over the input data simultaneously out-of-plane rotation, shift invariance and good clutter tolerance. It is able to successfully detect and classify correctly the true-class objects within background clutter for which there has been no previous training.

Post processing of optically recognized text via second order hidden Markov model

Science.gov (United States)

Poudel, Srijana

In this thesis, we describe a postprocessing system on Optical Character Recognition(OCR) generated text. Second Order Hidden Markov Model (HMM) approach is used to detect and correct the OCR related errors. The reason for choosing the 2nd order HMM is to keep track of the bigrams so that the model can represent the system more accurately. Based on experiments with training data of 159,733 characters and testing of 5,688 characters, the model was able to correct 43.38 % of the errors with a precision of 75.34 %. However, the precision value indicates that the model introduced some new errors, decreasing the correction percentage to 26.4%.

77 FR 71752 - Federal Motor Vehicle Safety Standards; Lamps, Reflective Devices, and Associated Equipment

Science.gov (United States)

2012-12-04

... Optical Character Recognition (OCR) process, thus allowing the agency to search and copy certain portions of your submissions.\\9\\ \\9\\ Optical character recognition (OCR) is the process of converting an image...

Automatic target recognition using a feature-based optical neural network

Science.gov (United States)

Chao, Tien-Hsin

1992-01-01

An optical neural network based upon the Neocognitron paradigm (K. Fukushima et al. 1983) is introduced. A novel aspect of the architectural design is shift-invariant multichannel Fourier optical correlation within each processing layer. Multilayer processing is achieved by iteratively feeding back the output of the feature correlator to the input spatial light modulator and updating the Fourier filters. By training the neural net with characteristic features extracted from the target images, successful pattern recognition with intra-class fault tolerance and inter-class discrimination is achieved. A detailed system description is provided. Experimental demonstration of a two-layer neural network for space objects discrimination is also presented.

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.

Electrooculography-based continuous eye-writing recognition system for efficient assistive communication systems.

Science.gov (United States)

Fang, Fuming; Shinozaki, Takahiro

2018-01-01

Human-computer interface systems whose input is based on eye movements can serve as a means of communication for patients with locked-in syndrome. Eye-writing is one such system; users can input characters by moving their eyes to follow the lines of the strokes corresponding to characters. Although this input method makes it easy for patients to get started because of their familiarity with handwriting, existing eye-writing systems suffer from slow input rates because they require a pause between input characters to simplify the automatic recognition process. In this paper, we propose a continuous eye-writing recognition system that achieves a rapid input rate because it accepts characters eye-written continuously, with no pauses. For recognition purposes, the proposed system first detects eye movements using electrooculography (EOG), and then a hidden Markov model (HMM) is applied to model the EOG signals and recognize the eye-written characters. Additionally, this paper investigates an EOG adaptation that uses a deep neural network (DNN)-based HMM. Experiments with six participants showed an average input speed of 27.9 character/min using Japanese Katakana as the input target characters. A Katakana character-recognition error rate of only 5.0% was achieved using 13.8 minutes of adaptation data.

Two-tier architecture for unconstrained handwritten character ...

Indian Academy of Sciences (India)

R. Narasimhan (Krishtel eMaging) 1461 1996 Oct 15 13:05:22

This approach uses the Kohonen self-organizing neural network for data classification in the ... Traditional classifiers test the ..... Trier O D, Jain A K, Taxt T 1996 Feature extraction methods for character recognition – A survey. Pattern Recogn.

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.

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.

Comparative implementation of Handwritten and Machine written Gurmukhi text utilizing appropriate parameters

Science.gov (United States)

Kaur, Jaswinder; Jagdev, Gagandeep, Dr.

2018-01-01

Optical character recognition is concerned with the recognition of optically processed characters. The recognition is done offline after the writing or printing has been completed, unlike online recognition where the computer has to recognize the characters instantly as they are drawn. The performance of character recognition depends upon the quality of scanned documents. The preprocessing steps are used for removing low-frequency background noise and normalizing the intensity of individual scanned documents. Several filters are used for reducing certain image details and enabling an easier or faster evaluation. The primary aim of the research work is to recognize handwritten and machine written characters and differentiate them. The language opted for the research work is Punjabi Gurmukhi and tool utilized is Matlab.

Automatic modulation format recognition for the next generation optical communication networks using artificial neural networks

Science.gov (United States)

Guesmi, Latifa; Hraghi, Abir; Menif, Mourad

2015-03-01

A new technique for Automatic Modulation Format Recognition (AMFR) in next generation optical communication networks is presented. This technique uses the Artificial Neural Network (ANN) in conjunction with the features of Linear Optical Sampling (LOS) of the detected signal at high bit rates using direct detection or coherent detection. The use of LOS method for this purpose mainly driven by the increase of bit rates which enables the measurement of eye diagrams. The efficiency of this technique is demonstrated under different transmission impairments such as chromatic dispersion (CD) in the range of -500 to 500 ps/nm, differential group delay (DGD) in the range of 0-15 ps and the optical signal tonoise ratio (OSNR) in the range of 10-30 dB. The results of numerical simulation for various modulation formats demonstrate successful recognition from a known bit rates with a higher estimation accuracy, which exceeds 99.8%.

Stress reaction process-based hierarchical recognition algorithm for continuous intrusion events in optical fiber prewarning system

Science.gov (United States)

Qu, Hongquan; Yuan, Shijiao; Wang, Yanping; Yang, Dan

2018-04-01

To improve the recognition performance of optical fiber prewarning system (OFPS), this study proposed a hierarchical recognition algorithm (HRA). Compared with traditional methods, which employ only a complex algorithm that includes multiple extracted features and complex classifiers to increase the recognition rate with a considerable decrease in recognition speed, HRA takes advantage of the continuity of intrusion events, thereby creating a staged recognition flow inspired by stress reaction. HRA is expected to achieve high-level recognition accuracy with less time consumption. First, this work analyzed the continuity of intrusion events and then presented the algorithm based on the mechanism of stress reaction. Finally, it verified the time consumption through theoretical analysis and experiments, and the recognition accuracy was obtained through experiments. Experiment results show that the processing speed of HRA is 3.3 times faster than that of a traditional complicated algorithm and has a similar recognition rate of 98%. The study is of great significance to fast intrusion event recognition in OFPS.

Page Recognition: Quantum Leap In Recognition Technology

Science.gov (United States)

Miller, Larry

1989-07-01

No milestone has proven as elusive as the always-approaching "year of the LAN," but the "year of the scanner" might claim the silver medal. Desktop scanners have been around almost as long as personal computers. And everyone thinks they are used for obvious desktop-publishing and business tasks like scanning business documents, magazine articles and other pages, and translating those words into files your computer understands. But, until now, the reality fell far short of the promise. Because it's true that scanners deliver an accurate image of the page to your computer, but the software to recognize this text has been woefully disappointing. Old optical-character recognition (OCR) software recognized such a limited range of pages as to be virtually useless to real users. (For example, one OCR vendor specified 12-point Courier font from an IBM Selectric typewriter: the same font in 10-point, or from a Diablo printer, was unrecognizable!) Computer dealers have told me the chasm between OCR expectations and reality is so broad and deep that nine out of ten prospects leave their stores in disgust when they learn the limitations. And this is a very important, very unfortunate gap. Because the promise of recognition -- what people want it to do -- carries with it tremendous improvements in our productivity and ability to get tons of written documents into our computers where we can do real work with it. The good news is that a revolutionary new development effort has led to the new technology of "page recognition," which actually does deliver the promise we've always wanted from OCR. I'm sure every reader appreciates the breakthrough represented by the laser printer and page-makeup software, a combination so powerful it created new reasons for buying a computer. A similar breakthrough is happening right now in page recognition: the Macintosh (and, I must admit, other personal computers) equipped with a moderately priced scanner and OmniPage software (from Caere

Digitizing Consumption Across the Operational Spectrum

Science.gov (United States)

2014-09-01

appropriate data storage method. 14. SUBJECT TERMS Logistics, relational database, non-relational database, NoSQL , optical character recognition...20  Figure 13.  NoSQL (key, value) Dictionary Example ........................................................21...recognition MRE Meal Ready to Eat NOSQL Not only SQL OCR optical character recognition PDF Portable Document Format QS query size RS result size

Target locations in visual field and character recognition by students of Chinese.

Science.gov (United States)

Chen, Yuan-Ho; Hsu, Sheng-Hsiung

2003-02-01

The potential influence of target location in a visual field on search should be considered in layouts of control panels and advertisements. This investigation was done to verify the assumption that the upper-left portion of a page or its equivalent naturally attracts the attention of the viewer. Exp. 1 used a tachistoscope to test which of eight Chinese characters first attracted the attention of viewers. The eight Chinese characters are arranged in a square and a circular configuration. In the square layout, a large square (18 cm x 18 cm) was first conceptually subdivided into nine equal parts (6 cm x 6 cm). Then, the eight Chinese characters were put in the center of each part, leaving the central part blank. In the circular layout, the same Chinese characters were symmetrically placed on the conceptual circumference (r = 6 cm) of a circle within a large square. Exp. 2 was a paper-and-pencil test. An embedded-fault-character-search was used to examine the location of the first faulty character discovered by the subjects. 60 college students and 36 schoolchildren were selected as subjects for the tachistoscopic experiment and paper-and-pencil test. Finally, five graduate students participated in Exp. 3 in which an eye camera registered subjects' eye movements to measured distribution of durations of looking over eight locations. The measurements indicated a slight predominance of the upper-left portion for college students and graduate students, and a slight predominance of the upper-right portion for schoolchildren.

Automatic Number Plate Recognition System for IPhone Devices

Directory of Open Access Journals (Sweden)

Călin Enăchescu

2013-06-01

Full Text Available This paper presents a system for automatic number plate recognition, implemented for devices running the iOS operating system. The methods used for number plate recognition are based on existing methods, but optimized for devices with low hardware resources. To solve the task of automatic number plate recognition we have divided it into the following subtasks: image acquisition, localization of the number plate position on the image and character detection. The first subtask is performed by the camera of an iPhone, the second one is done using image pre-processing methods and template matching. For the character recognition we are using a feed-forward artificial neural network. Each of these methods is presented along with its results.

Artificial fingerprint recognition by using optical coherence tomography with autocorrelation analysis

Science.gov (United States)

Cheng, Yezeng; Larin, Kirill V.

2006-12-01

Fingerprint recognition is one of the most widely used methods of biometrics. This method relies on the surface topography of a finger and, thus, is potentially vulnerable for spoofing by artificial dummies with embedded fingerprints. In this study, we applied the optical coherence tomography (OCT) technique to distinguish artificial materials commonly used for spoofing fingerprint scanning systems from the real skin. Several artificial fingerprint dummies made from household cement and liquid silicone rubber were prepared and tested using a commercial fingerprint reader and an OCT system. While the artificial fingerprints easily spoofed the commercial fingerprint reader, OCT images revealed the presence of them at all times. We also demonstrated that an autocorrelation analysis of the OCT images could be potentially used in automatic recognition systems.

Intrusion recognition for optic fiber vibration sensor based on the selective attention mechanism

Science.gov (United States)

Xu, Haiyan; Xie, Yingjuan; Li, Min; Zhang, Zhuo; Zhang, Xuewu

2017-11-01

Distributed fiber-optic vibration sensors receive extensive investigation and play a significant role in the sensor panorama. A fiber optic perimeter detection system based on all-fiber interferometric sensor is proposed, through the back-end analysis, processing and intelligent identification, which can distinguish effects of different intrusion activities. In this paper, an intrusion recognition based on the auditory selective attention mechanism is proposed. Firstly, considering the time-frequency of vibration, the spectrogram is calculated. Secondly, imitating the selective attention mechanism, the color, direction and brightness map of the spectrogram is computed. Based on these maps, the feature matrix is formed after normalization. The system could recognize the intrusion activities occurred along the perimeter sensors. Experiment results show that the proposed method for the perimeter is able to differentiate intrusion signals from ambient noises. What's more, the recognition rate of the system is improved while deduced the false alarm rate, the approach is proved by large practical experiment and project.

Target recognition by wavelet transform

International Nuclear Information System (INIS)

Li Zhengdong; He Wuliang; Zheng Xiaodong; Cheng Jiayuan; Peng Wen; Pei Chunlan; Song Chen

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

Classification and recognition of handwritten digits by using ...

Indian Academy of Sciences (India)

The problem of handwriting recognition has been studied for decades and ... tially completed work of character recognition using mathematical morphology. ... There are ten digits in English language and each digit is differentiated from the ...

Muscle Sensor Model Using Small Scale Optical Device for Pattern Recognitions

Directory of Open Access Journals (Sweden)

Kreangsak Tamee

2013-01-01

Full Text Available A new sensor system for measuring contraction and relaxation of muscles by using a PANDA ring resonator is proposed. The small scale optical device is designed and configured to perform the coupling effects between the changes in optical device phase shift and human facial muscle movement, which can be used to form the relationship between optical phase shift and muscle movement. By using the Optiwave and MATLAB programs, the results obtained have shown that the measurement of the contraction and relaxation of muscles can be obtained after the muscle movements, in which the unique pattern of individual muscle movement from facial expression can be established. The obtained simulation results, that is, interference signal patterns, can be used to form the various pattern recognitions, which are useful for the human machine interface and the human computer interface application and discussed in detail.

Text recognition and correction for automated data collection by mobile devices

Science.gov (United States)

Ozarslan, Suleyman; Eren, P. Erhan

2014-03-01

Participatory sensing is an approach which allows mobile devices such as mobile phones to be used for data collection, analysis and sharing processes by individuals. Data collection is the first and most important part of a participatory sensing system, but it is time consuming for the participants. In this paper, we discuss automatic data collection approaches for reducing the time required for collection, and increasing the amount of collected data. In this context, we explore automated text recognition on images of store receipts which are captured by mobile phone cameras, and the correction of the recognized text. Accordingly, our first goal is to evaluate the performance of the Optical Character Recognition (OCR) method with respect to data collection from store receipt images. Images captured by mobile phones exhibit some typical problems, and common image processing methods cannot handle some of them. Consequently, the second goal is to address these types of problems through our proposed Knowledge Based Correction (KBC) method used in support of the OCR, and also to evaluate the KBC method with respect to the improvement on the accurate recognition rate. Results of the experiments show that the KBC method improves the accurate data recognition rate noticeably.

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.

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

A Study Of The Effects Of Computer Animated Character Body Style On Perception Of Facial Expression

OpenAIRE

Cissell, Katherine

2013-01-01

This study examined if there is a difference in viewer perception of computer animated character facial expressions based on character body style, specifically, realistic and stylized character body styles. Participants viewed twenty clips of computer animated characters expressing one of five emotions: sadness, happiness, anger, surprise and fear. They then named the emotion and rated the sincerity, intensity, and typicality of each clip. The results indicated that for recognition, participa...

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.

Differential theory of learning for efficient neural network pattern recognition

Science.gov (United States)

Hampshire, John B., II; Vijaya Kumar, Bhagavatula

1993-09-01

We describe a new theory of differential learning by which a broad family of pattern classifiers (including many well-known neural network paradigms) can learn stochastic concepts efficiently. We describe the relationship between a classifier's ability to generate well to unseen test examples and the efficiency of the strategy by which it learns. We list a series of proofs that differential learning is efficient in its information and computational resource requirements, whereas traditional probabilistic learning strategies are not. The proofs are illustrated by a simple example that lends itself to closed-form analysis. We conclude with an optical character recognition task for which three different types of differentially generated classifiers generalize significantly better than their probabilistically generated counterparts.

Compact holographic optical neural network system for real-time pattern recognition

Science.gov (United States)

Lu, Taiwei; Mintzer, David T.; Kostrzewski, Andrew A.; Lin, Freddie S.

1996-08-01

One of the important characteristics of artificial neural networks is their capability for massive interconnection and parallel processing. Recently, specialized electronic neural network processors and VLSI neural chips have been introduced in the commercial market. The number of parallel channels they can handle is limited because of the limited parallel interconnections that can be implemented with 1D electronic wires. High-resolution pattern recognition problems can require a large number of neurons for parallel processing of an image. This paper describes a holographic optical neural network (HONN) that is based on high- resolution volume holographic materials and is capable of performing massive 3D parallel interconnection of tens of thousands of neurons. A HONN with more than 16,000 neurons packaged in an attache case has been developed. Rotation- shift-scale-invariant pattern recognition operations have been demonstrated with this system. System parameters such as the signal-to-noise ratio, dynamic range, and processing speed are discussed.

Binary zone-plate array for a parallel joint transform correlator applied to face recognition.

Science.gov (United States)

Kodate, K; Hashimoto, A; Thapliya, R

1999-05-10

Taking advantage of small aberrations, high efficiency, and compactness, we developed a new, to our knowledge, design procedure for a binary zone-plate array (BZPA) and applied it to a parallel joint transform correlator for the recognition of the human face. Pairs of reference and unknown images of faces are displayed on a liquid-crystal spatial light modulator (SLM), Fourier transformed by the BZPA, intensity recorded on an optically addressable SLM, and inversely Fourier transformed to obtain correlation signals. Consideration of the bandwidth allows the relations among the channel number, the numerical aperture of the zone plates, and the pattern size to be determined. Experimentally a five-channel parallel correlator was implemented and tested successfully with a 100-person database. The design and the fabrication of a 20-channel BZPA for phonetic character recognition are also included.

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.

Learning through hand- or typewriting influences visual recognition of new graphic shapes: behavioral and functional imaging evidence.

Science.gov (United States)

Longcamp, Marieke; Boucard, Céline; Gilhodes, Jean-Claude; Anton, Jean-Luc; Roth, Muriel; Nazarian, Bruno; Velay, Jean-Luc

2008-05-01

Fast and accurate visual recognition of single characters is crucial for efficient reading. We explored the possible contribution of writing memory to character recognition processes. We evaluated the ability of adults to discriminate new characters from their mirror images after being taught how to produce the characters either by traditional pen-and-paper writing or with a computer keyboard. After training, we found stronger and longer lasting (several weeks) facilitation in recognizing the orientation of characters that had been written by hand compared to those typed. Functional magnetic resonance imaging recordings indicated that the response mode during learning is associated with distinct pathways during recognition of graphic shapes. Greater activity related to handwriting learning and normal letter identification was observed in several brain regions known to be involved in the execution, imagery, and observation of actions, in particular, the left Broca's area and bilateral inferior parietal lobules. Taken together, these results provide strong arguments in favor of the view that the specific movements memorized when learning how to write participate in the visual recognition of graphic shapes and letters.

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.

Monitoring of facial stress during space flight: Optical computer recognition combining discriminative and generative methods

Science.gov (United States)

Dinges, David F.; Venkataraman, Sundara; McGlinchey, Eleanor L.; Metaxas, Dimitris N.

2007-02-01

Astronauts are required to perform mission-critical tasks at a high level of functional capability throughout spaceflight. Stressors can compromise their ability to do so, making early objective detection of neurobehavioral problems in spaceflight a priority. Computer optical approaches offer a completely unobtrusive way to detect distress during critical operations in space flight. A methodology was developed and a study completed to determine whether optical computer recognition algorithms could be used to discriminate facial expressions during stress induced by performance demands. Stress recognition from a facial image sequence is a subject that has not received much attention although it is an important problem for many applications beyond space flight (security, human-computer interaction, etc.). This paper proposes a comprehensive method to detect stress from facial image sequences by using a model-based tracker. The image sequences were captured as subjects underwent a battery of psychological tests under high- and low-stress conditions. A cue integration-based tracking system accurately captured the rigid and non-rigid parameters of different parts of the face (eyebrows, lips). The labeled sequences were used to train the recognition system, which consisted of generative (hidden Markov model) and discriminative (support vector machine) parts that yield results superior to using either approach individually. The current optical algorithm methods performed at a 68% accuracy rate in an experimental study of 60 healthy adults undergoing periods of high-stress versus low-stress performance demands. Accuracy and practical feasibility of the technique is being improved further with automatic multi-resolution selection for the discretization of the mask, and automated face detection and mask initialization algorithms.

BACS: The Brussels Artificial Character Sets for studies in cognitive psychology and neuroscience.

Science.gov (United States)

Vidal, Camille; Content, Alain; Chetail, Fabienne

2017-12-01

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.

Compact holographic memory and its application to optical pattern recognition

Science.gov (United States)

Chao, Tien-Hsin; Reyes, George F.; Zhou, Hanying

2001-03-01

JPL is developing a high-density, nonvolatile Compact Holographic Data Storage (CHDS) system to enable large- capacity, high-speed, low power consumption, and read/write of data for commercial and space applications. This CHDS system consists of laser diodes, photorefractive crystal, spatial light modulator, photodetector array, and I/O electronic interface. In operation, pages of information would be recorded and retrieved with random access and high- speed. In this paper, recent technology progress in developing this CHDS at JPL will be presented. The recent applications of the CHDS to optical pattern recognition, as a high-density, high transfer rate memory bank will also be discussed.

Chinese Characters Elicit Face-Like N170 Inversion Effects

Science.gov (United States)

Wang, Man-Ying; Kuo, Bo-Cheng; Cheng, Shih-Kuen

2011-01-01

Recognition of both faces and Chinese characters is commonly believed to rely on configural information. While faces typically exhibit behavioral and N170 inversion effects that differ from non-face stimuli (Rossion, Joyce, Cottrell, & Tarr, 2003), the current study examined whether a similar reliance on configural processing may result in similar…

Tunability of Open-Shell Character, Charge Asymmetry, and Third-Order Nonlinear Optical Properties of Covalently Linked (Hetero)Phenalenyl Dimers.

Science.gov (United States)

Minamida, Yuka; Kishi, Ryohei; Fukuda, Kotaro; Matsui, Hiroshi; Takamuku, Shota; Yamane, Masaki; Tonami, Takayoshi; Nakano, Masayoshi

2018-02-06

Tunability of the open-shell character, charge asymmetry, and third-order nonlinear optical (NLO) properties of covalently linked (hetero)phenalenyl dimers are investigated by using the density functional theory method. By changing the molecular species X and substitution position (i, j) for the linker part, a variety of intermonomer distances R and relative alignments between the phenalenyl dimers can be realized from the geometry optimizations, resulting in a wide-range tuning of diradical character y and charge asymmetry. It is found that the static second hyperpolarizabilities along the stacking direction, γ yyyy , are one-order enhanced for phenalenyl dimer systems exhibiting intermediate y, a feature that is in good agreement with the "y-γ correlation". By replacing the central carbon atoms of the phenalenyl rings with a boron or a nitrogen, we have also designed covalently linked heterophenalenyl dimers. The introduction of such a charge asymmetry to the open-shell systems, which leads to closed-shell ionic ground states, is found to further enhance the γ yyyy values of the systems having longer intermonomer distance R with intermediate ionic character, that is, charge asymmetry. The present results demonstrate a promising potential of covalently linked NLO dimers with intermediate open-shell/ionic characters as a new building block of highly efficient NLO systems. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

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.

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.

Tune in to the Tone: Lexical Tone Identification is Associated with Vocabulary and Word Recognition Abilities in Young Chinese Children.

Science.gov (United States)

Tong, Xiuli; Tong, Xiuhong; McBride-Chang, Catherine

2015-12-01

Lexical tone is one of the most prominent features in the phonological representation of words in Chinese. However, little, if any, research to date has directly evaluated how young Chinese children's lexical tone identification skills contribute to vocabulary acquisition and character recognition. The present study distinguished lexical tones from segmental phonological awareness and morphological awareness in order to estimate the unique contribution of lexical tone in early vocabulary acquisition and character recognition. A sample of 199 Cantonese children aged 5-6 years was assessed on measures of lexical tone identification, segmental phonological awareness, morphological awareness, nonverbal ability, vocabulary knowledge, and Chinese character recognition. It was found that lexical tone awareness and morphological awareness were both associated with vocabulary knowledge and character recognition. However, there was a significant relationship between lexical tone awareness and both vocabulary knowledge and character recognition, even after controlling for the effects of age, nonverbal ability, segmental phonological awareness and morphological awareness. These findings suggest that lexical tone is a key factor accounting for individual variance in young children's lexical acquisition in Chinese, and that lexical tone should be considered in understanding how children learn new Chinese vocabulary words, in either oral or written forms.

An Edge-Based Macao License Plate Recognition System

Directory of Open Access Journals (Sweden)

Chi-Man Pun

2011-04-01

Full Text Available This paper presents a system to recognize Macao license plates. Sobel edge detector is employed to extract the vertical edges, and an edge composition algorithm is proposed to combine the edges into candidate plate regions. They are further examined on the existence of the character qMq by a verification algorithm. A row separation algorithm is also proposed to cater both one-row and two-row types of plates. Projection analysis and template matching methods are exploited to segment and recognize the characters. Various pre and post processing steps are proposed other than traditional implementation so as to improve the recognition accuracy. This work achieves a high recognition rate of 95%.

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 �

Effects on Learning Logographic Character Formation in Computer-Assisted Handwriting Instruction

Science.gov (United States)

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…

Massive parallel optical pattern recognition and retrieval via a two-stage high-capacity multichannel holographic random access memory system

International Nuclear Information System (INIS)

Cai, Luzhong; Liu, Hua-Kuang

2000-01-01

The multistage holographic optical random access memory (HORAM) system reported recently by Liu et al. provides a new degree of freedom for improving storage capacity. We further present a theoretical and practical analysis of the HORAM system with experimental results. Our discussions include the system design and geometrical requirements, its applications for multichannel pattern recognition and associative memory, the 2-D and 3-D information storage capacity, and multichannel image storage and retrieval via VanderLugt correlator (VLC) filters and joint transform holograms. A series of experiments are performed to demonstrate the feasibility of the multichannel pattern recognition and image retrieval with both the VLC and joint transform correlator (JTC) architectures. The experimental results with as many as 2025 channels show good agreement with the theoretical analysis. (c) 2000 Society of Photo-Optical Instrumentation Engineers

Personality and emotion-based high-level control of affective story characters.

Science.gov (United States)

Su, Wen-Poh; Pham, Binh; Wardhani, Aster

2007-01-01

Human emotional behavior, personality, and body language are the essential elements in the recognition of a believable synthetic story character. This paper presents an approach using story scripts and action descriptions in a form similar to the content description of storyboards to predict specific personality and emotional states. By adopting the Abridged Big Five Circumplex (AB5C) Model of personality from the study of psychology as a basis for a computational model, we construct a hierarchical fuzzy rule-based system to facilitate the personality and emotion control of the body language of a dynamic story character. The story character can consistently perform specific postures and gestures based on his/her personality type. Story designers can devise a story context in the form of our story interface which predictably motivates personality and emotion values to drive the appropriate movements of the story characters. Our system takes advantage of relevant knowledge described by psychologists and researchers of storytelling, nonverbal communication, and human movement. Our ultimate goal is to facilitate the high-level control of a synthetic character.

Transformation de Fourier et moments invariants appliqués à la reconnaissance des caractères Tifinaghe

Directory of Open Access Journals (Sweden)

Rachid El Ayachi

2012-03-01

Full Text Available Optical Character Recognition OCR is a tool that aims to provide opportunities for computers to read characters without human intervention. The objective of OCR is characterization of a character by invariant descriptors in translation, rotation and scaling. In this paper, the OCR developed use invariant moments and Fourier transform in extraction phase. In the recognition phase, dynamic programming and neural network are adopted. All tests are applied on Tifinaghe printed characters.

Robust keyword retrieval method for OCRed text

Science.gov (United States)

Fujii, Yusaku; Takebe, Hiroaki; Tanaka, Hiroshi; Hotta, Yoshinobu

2011-01-01

Document management systems have become important because of the growing popularity of electronic filing of documents and scanning of books, magazines, manuals, etc., through a scanner or a digital camera, for storage or reading on a PC or an electronic book. Text information acquired by optical character recognition (OCR) is usually added to the electronic documents for document retrieval. Since texts generated by OCR generally include character recognition errors, robust retrieval methods have been introduced to overcome this problem. In this paper, we propose a retrieval method that is robust against both character segmentation and recognition errors. In the proposed method, the insertion of noise characters and dropping of characters in the keyword retrieval enables robustness against character segmentation errors, and character substitution in the keyword of the recognition candidate for each character in OCR or any other character enables robustness against character recognition errors. The recall rate of the proposed method was 15% higher than that of the conventional method. However, the precision rate was 64% lower.

Application of optical character recognition in thermal image processing

Science.gov (United States)

Chan, W. T.; Sim, K. S.; Tso, C. P.

2011-07-01

This paper presents the results of a study on the reliability of the thermal imager compared to other devices that are used in preventive maintenance. Several case studies are used to facilitate the comparisons. When any device is found to perform unsatisfactorily where there is a suspected fault, its short-fall is determined so that the other devices may compensate, if possible. This study discovered that the thermal imager is not suitable or efficient enough for systems that happen to have little contrast in temperature between its parts or small but important parts that have their heat signatures obscured by those from other parts. The thermal imager is also found to be useful for preliminary examinations of certain systems, after which other more economical devices are suitable substitutes for further examinations. The findings of this research will be useful to the design and planning of preventive maintenance routines for industrial benefits.

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.

Advances in oriental document analysis and recognition techniques

CERN Document Server

Lee, Seong-Whan

1999-01-01

In recent years, rapid progress has been made in computer processing of oriental languages, and the research developments in this area have resulted in tremendous changes in handwriting processing, printed oriental character recognition, document analysis and recognition, automatic input methodologies for oriental languages, etc. Advances in computer processing of oriental languages can also be seen in multimedia computing and the World Wide Web. Many of the results in those domains are presented in this book.

Description and recognition of patterns in stochastic signals. [Electroencephalograms

Energy Technology Data Exchange (ETDEWEB)

Flik, T [Technische Univ. Berlin (F.R. Germany). Informatik-Forschungsgruppe Rechnerorganisation und Schaltwerke

1975-10-01

A method is shown for the description and recognition of patterns in stochastic signals such as electroencephalograms. For pattern extraction the signal is segmented at times of minimum amplitudes. The describing features consist of geometric values of the so defined patterns. The classification algorithm is based on the regression analysis, which is well known in the field of character recognition. For an economic classification a method is proposed which reduces the number of features. The quality of this pattern recognition method is demonstrated by the detection of spike wave complexes in electroencephalograms. The pattern description and recognition are provided for processing on a digital computer. (DE)

Type-2 fuzzy graphical models for pattern recognition

CERN Document Server

Zeng, Jia

2015-01-01

This book discusses how to combine type-2 fuzzy sets and graphical models to solve a range of real-world pattern recognition problems such as speech recognition, handwritten Chinese character recognition, topic modeling as well as human action recognition. It covers these recent developments while also providing a comprehensive introduction to the fields of type-2 fuzzy sets and graphical models. Though primarily intended for graduate students, researchers and practitioners in fuzzy logic and pattern recognition, the book can also serve as a valuable reference work for researchers without any previous knowledge of these fields. Dr. Jia Zeng is a Professor at the School of Computer Science and Technology, Soochow University, China. Dr. Zhi-Qiang Liu is a Professor at the School of Creative Media, City University of Hong Kong, China.

Toward a multipoint optical fibre sensor system for use in process water systems based on artificial neural network pattern recognition

International Nuclear Information System (INIS)

King, D; Lyons, W B; Flanagan, C; Lewis, E

2005-01-01

An optical fibre sensor capable of detecting various concentrations of ethanol in water supplies is reported. The sensor is based on a U-bend sensor configuration and is incorporated into a 170-metre length of silica cladding silica core optical fibre. The sensor is interrogated using Optical Time Domain Reflectometry (OTDR) and it is proposed to apply artificial neural network (ANN) pattern recognition techniques to the resulting OTDR signals to accurately classify the sensor test conditions. It is also proposed that additional U-bend configuration sensors will be added to the fibre measurement length, in order to implement a multipoint optical fibre sensor system

Shift-, rotation-, and scale-invariant shape recognition system using an optical Hough transform

Science.gov (United States)

Schmid, Volker R.; Bader, Gerhard; Lueder, Ernst H.

1998-02-01

We present a hybrid shape recognition system with an optical Hough transform processor. The features of the Hough space offer a separate cancellation of distortions caused by translations and rotations. Scale invariance is also provided by suitable normalization. The proposed system extends the capabilities of Hough transform based detection from only straight lines to areas bounded by edges. A very compact optical design is achieved by a microlens array processor accepting incoherent light as direct optical input and realizing the computationally expensive connections massively parallel. Our newly developed algorithm extracts rotation and translation invariant normalized patterns of bright spots on a 2D grid. A neural network classifier maps the 2D features via a nonlinear hidden layer onto the classification output vector. We propose initialization of the connection weights according to regions of activity specifically assigned to each neuron in the hidden layer using a competitive network. The presented system is designed for industry inspection applications. Presently we have demonstrated detection of six different machined parts in real-time. Our method yields very promising detection results of more than 96% correctly classified parts.

Fast cat-eye effect target recognition based on saliency extraction

Science.gov (United States)

Li, Li; Ren, Jianlin; Wang, Xingbin

2015-09-01

Background complexity is a main reason that results in false detection in cat-eye target recognition. Human vision has selective attention property which can help search the salient target from complex unknown scenes quickly and precisely. In the paper, we propose a novel cat-eye effect target recognition method named Multi-channel Saliency Processing before Fusion (MSPF). This method combines traditional cat-eye target recognition with the selective characters of visual attention. Furthermore, parallel processing enables it to achieve fast recognition. Experimental results show that the proposed method performs better in accuracy, robustness and speed compared to other methods.

Interspecific aggression, not interspecific mating, drives character displacement in the wing coloration of male rubyspot damselflies (Hetaerina)

Science.gov (United States)

Drury, J. P.; Grether, G. F.

2014-01-01

Traits that mediate intraspecific social interactions may overlap in closely related sympatric species, resulting in costly between-species interactions. Such interactions have principally interested investigators studying the evolution of reproductive isolation via reproductive character displacement (RCD) or reinforcement, yet in addition to reproductive interference, interspecific trait overlap can lead to costly between-species aggression. Previous research on rubyspot damselflies (Hetaerina spp.) demonstrated that sympatric shifts in male wing colour patterns and competitor recognition reduce interspecific aggression, supporting the hypothesis that agonistic character displacement (ACD) drove trait shifts. However, a recent theoretical model shows that RCD overshadows ACD if the same male trait is used for both female mate recognition and male competitor recognition. To determine whether female mate recognition is based on male wing coloration in Hetaerina, we conducted a phenotype manipulation experiment. Compared to control males, male H. americana with wings manipulated to resemble a sympatric congener (H. titia) suffered no reduction in mating success. Thus, female mate recognition is not based on species differences in male wing coloration. Experimental males did, however, experience higher interspecific fighting rates and reduced survival compared to controls. These results greatly strengthen the case for ACD and highlight the mechanistic distinction between ACD and RCD. PMID:25339724

Pattern Recognition in Optical Remote Sensing Data Processing

Science.gov (United States)

Kozoderov, Vladimir; Kondranin, Timofei; Dmitriev, Egor; Kamentsev, Vladimir

Computational procedures of the land surface biophysical parameters retrieval imply that modeling techniques are available of the outgoing radiation description together with monitoring techniques of remote sensing data processing using registered radiances between the related optical sensors and the land surface objects called “patterns”. Pattern recognition techniques are a valuable approach to the processing of remote sensing data for images of the land surface - atmosphere system. Many simplified codes of the direct and inverse problems of atmospheric optics are considered applicable for the imagery processing of low and middle spatial resolution. Unless the authors are not interested in the accuracy of the final information products, they utilize these standard procedures. The emerging necessity of processing data of high spectral and spatial resolution given by imaging spectrometers puts forward the newly defined pattern recognition techniques. The proposed tools of using different types of classifiers combined with the parameter retrieval procedures for the forested environment are maintained to have much wider applications as compared with the image features and object shapes extraction, which relates to photometry and geometry in pixel-level reflectance representation of the forested land cover. The pixel fraction and reflectance of “end-members” (sunlit forest canopy, sunlit background and shaded background for a particular view and solar illumination angle) are only a part in the listed techniques. It is assumed that each pixel views collections of the individual forest trees and the pixel-level reflectance can thus be computed as a linear mixture of sunlit tree tops, sunlit background (or understory) and shadows. Instead of these photometry and geometry constraints, the improved models are developed of the functional description of outgoing spectral radiation, in which such parameters of the forest canopy like the vegetation biomass density for

Star pattern recognition algorithm aided by inertial information

Science.gov (United States)

Liu, Bao; Wang, Ke-dong; Zhang, Chao

2011-08-01

Star pattern recognition is one of the key problems of the celestial navigation. The traditional star pattern recognition approaches, such as the triangle algorithm and the star angular distance algorithm, are a kind of all-sky matching method whose recognition speed is slow and recognition success rate is not high. Therefore, the real time and reliability of CNS (Celestial Navigation System) is reduced to some extent, especially for the maneuvering spacecraft. However, if the direction of the camera optical axis can be estimated by other navigation systems such as INS (Inertial Navigation System), the star pattern recognition can be fulfilled in the vicinity of the estimated direction of the optical axis. The benefits of the INS-aided star pattern recognition algorithm include at least the improved matching speed and the improved success rate. In this paper, the direction of the camera optical axis, the local matching sky, and the projection of stars on the image plane are estimated by the aiding of INS firstly. Then, the local star catalog for the star pattern recognition is established in real time dynamically. The star images extracted in the camera plane are matched in the local sky. Compared to the traditional all-sky star pattern recognition algorithms, the memory of storing the star catalog is reduced significantly. Finally, the INS-aided star pattern recognition algorithm is validated by simulations. The results of simulations show that the algorithm's computation time is reduced sharply and its matching success rate is improved greatly.

Speech Recognition Technology for Disabilities Education

Science.gov (United States)

Tang, K. Wendy; Kamoua, Ridha; Sutan, Victor; Farooq, Omer; Eng, Gilbert; Chu, Wei Chern; Hou, Guofeng

2005-01-01

Speech recognition is an alternative to traditional methods of interacting with a computer, such as textual input through a keyboard. An effective system can replace or reduce the reliability on standard keyboard and mouse input. This can especially assist dyslexic students who have problems with character or word use and manipulation in a textual…

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.

Bidirectional Modulation of Recognition Memory.

Science.gov (United States)

Ho, Jonathan W; Poeta, Devon L; Jacobson, Tara K; Zolnik, Timothy A; Neske, Garrett T; Connors, Barry W; Burwell, Rebecca D

2015-09-30

Perirhinal cortex (PER) has a well established role in the familiarity-based recognition of individual items and objects. For example, animals and humans with perirhinal damage are unable to distinguish familiar from novel objects in recognition memory tasks. In the normal brain, perirhinal neurons respond to novelty and familiarity by increasing or decreasing firing rates. Recent work also implicates oscillatory activity in the low-beta and low-gamma frequency bands in sensory detection, perception, and recognition. Using optogenetic methods in a spontaneous object exploration (SOR) task, we altered recognition memory performance in rats. In the SOR task, normal rats preferentially explore novel images over familiar ones. We modulated exploratory behavior in this task by optically stimulating channelrhodopsin-expressing perirhinal neurons at various frequencies while rats looked at novel or familiar 2D images. Stimulation at 30-40 Hz during looking caused rats to treat a familiar image as if it were novel by increasing time looking at the image. Stimulation at 30-40 Hz was not effective in increasing exploration of novel images. Stimulation at 10-15 Hz caused animals to treat a novel image as familiar by decreasing time looking at the image, but did not affect looking times for images that were already familiar. We conclude that optical stimulation of PER at different frequencies can alter visual recognition memory bidirectionally. Significance statement: Recognition of novelty and familiarity are important for learning, memory, and decision making. Perirhinal cortex (PER) has a well established role in the familiarity-based recognition of individual items and objects, but how novelty and familiarity are encoded and transmitted in the brain is not known. Perirhinal neurons respond to novelty and familiarity by changing firing rates, but recent work suggests that brain oscillations may also be important for recognition. In this study, we showed that stimulation of

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

Younger and Older Users’ Recognition of Virtual Agent Facial Expressions

Science.gov (United States)

Beer, Jenay M.; Smarr, Cory-Ann; Fisk, Arthur D.; Rogers, Wendy A.

2015-01-01

As technology advances, robots and virtual agents will be introduced into the home and healthcare settings to assist individuals, both young and old, with everyday living tasks. Understanding how users recognize an agent’s social cues is therefore imperative, especially in social interactions. Facial expression, in particular, is one of the most common non-verbal cues used to display and communicate emotion in on-screen agents (Cassell, Sullivan, Prevost, & Churchill, 2000). Age is important to consider because age-related differences in emotion recognition of human facial expression have been supported (Ruffman et al., 2008), with older adults showing a deficit for recognition of negative facial expressions. Previous work has shown that younger adults can effectively recognize facial emotions displayed by agents (Bartneck & Reichenbach, 2005; Courgeon et al. 2009; 2011; Breazeal, 2003); however, little research has compared in-depth younger and older adults’ ability to label a virtual agent’s facial emotions, an import consideration because social agents will be required to interact with users of varying ages. If such age-related differences exist for recognition of virtual agent facial expressions, we aim to understand if those age-related differences are influenced by the intensity of the emotion, dynamic formation of emotion (i.e., a neutral expression developing into an expression of emotion through motion), or the type of virtual character differing by human-likeness. Study 1 investigated the relationship between age-related differences, the implication of dynamic formation of emotion, and the role of emotion intensity in emotion recognition of the facial expressions of a virtual agent (iCat). Study 2 examined age-related differences in recognition expressed by three types of virtual characters differing by human-likeness (non-humanoid iCat, synthetic human, and human). Study 2 also investigated the role of configural and featural processing as a

64 x 64 thresholding photodetector array for optical pattern recognition

Science.gov (United States)

Langenbacher, Harry; Chao, Tien-Hsin; Shaw, Timothy; Yu, Jeffrey W.

1993-10-01

A high performance 32 X 32 peak detector array is introduced. This detector consists of a 32 X 32 array of thresholding photo-transistor cells, manufactured with a standard MOSIS digital 2-micron CMOS process. A built-in thresholding function that is able to perform 1024 thresholding operations in parallel strongly distinguishes this chip from available CCD detectors. This high speed detector offers responses from one to 10 milliseconds that is much higher than the commercially available CCD detectors operating at a TV frame rate. The parallel multiple peaks thresholding detection capability makes it particularly suitable for optical correlator and optoelectronically implemented neural networks. The principle of operation, circuit design and the performance characteristics are described. Experimental demonstration of correlation peak detection is also provided. Recently, we have also designed and built an advanced version of a 64 X 64 thresholding photodetector array chip. Experimental investigation of using this chip for pattern recognition is ongoing.

Improved information processing and dissemination through the introduction of new technology

Energy Technology Data Exchange (ETDEWEB)

Spath, C E; Marsh, Jr, F E

1983-10-01

This paper discusses the following topic on information technology: technology signals a liberation; application of information technology; optical character recognition; optical memories; and planning considerations and the future.

Methods for Presenting Braille Characters on a Mobile Device with a Touchscreen and Tactile Feedback.

Science.gov (United States)

Rantala, J; Raisamo, R; Lylykangas, J; Surakka, V; Raisamo, J; Salminen, K; Pakkanen, T; Hippula, A

2009-01-01

Three novel interaction methods were designed for reading six-dot Braille characters from the touchscreen of a mobile device. A prototype device with a piezoelectric actuator embedded under the touchscreen was used to create tactile feedback. The three interaction methods, scan, sweep, and rhythm, enabled users to read Braille characters one at a time either by exploring the characters dot by dot or by sensing a rhythmic pattern presented on the screen. The methods were tested with five blind Braille readers as a proof of concept. The results of the first experiment showed that all three methods can be used to convey information as the participants could accurately (91-97 percent) recognize individual characters. In the second experiment the presentation rate of the most efficient and preferred method, the rhythm, was varied. A mean recognition accuracy of 70 percent was found when the speed of presenting a single character was nearly doubled from the first experiment. The results showed that temporal tactile feedback and Braille coding can be used to transmit single-character information while further studies are still needed to evaluate the presentation of serial information, i.e., multiple Braille characters.

Analysis of Documentation Speed Using Web-Based Medical Speech Recognition Technology: Randomized Controlled Trial.

Science.gov (United States)

Vogel, Markus; Kaisers, Wolfgang; Wassmuth, Ralf; Mayatepek, Ertan

2015-11-03

Clinical documentation has undergone a change due to the usage of electronic health records. The core element is to capture clinical findings and document therapy electronically. Health care personnel spend a significant portion of their time on the computer. Alternatives to self-typing, such as speech recognition, are currently believed to increase documentation efficiency and quality, as well as satisfaction of health professionals while accomplishing clinical documentation, but few studies in this area have been published to date. This study describes the effects of using a Web-based medical speech recognition system for clinical documentation in a university hospital on (1) documentation speed, (2) document length, and (3) physician satisfaction. Reports of 28 physicians were randomized to be created with (intervention) or without (control) the assistance of a Web-based system of medical automatic speech recognition (ASR) in the German language. The documentation was entered into a browser's text area and the time to complete the documentation including all necessary corrections, correction effort, number of characters, and mood of participant were stored in a database. The underlying time comprised text entering, text correction, and finalization of the documentation event. Participants self-assessed their moods on a scale of 1-3 (1=good, 2=moderate, 3=bad). Statistical analysis was done using permutation tests. The number of clinical reports eligible for further analysis stood at 1455. Out of 1455 reports, 718 (49.35%) were assisted by ASR and 737 (50.65%) were not assisted by ASR. Average documentation speed without ASR was 173 (SD 101) characters per minute, while it was 217 (SD 120) characters per minute using ASR. The overall increase in documentation speed through Web-based ASR assistance was 26% (P=.04). Participants documented an average of 356 (SD 388) characters per report when not assisted by ASR and 649 (SD 561) characters per report when assisted

Container code recognition in information auto collection system of container inspection

International Nuclear Information System (INIS)

Su Jianping; Chen Zhiqiang; Zhang Li; Gao Wenhuan; Kang Kejun

2003-01-01

Now custom needs electrical application and automatic detection. Container inspection should not only give the image of the goods, but also auto-attain container's code and weight. Its function and track control, information transfer make up the Information Auto Collection system of Container Inspection. Code Recognition is the point. The article is based on model match, the close property of character, and uses it to recognize. Base on checkout rule, design the adjustment arithmetic, form the whole recognition strategy. This strategy can achieve high recognition ratio and robust property

Semi-automated contour recognition using DICOMautomaton

International Nuclear Information System (INIS)

Clark, H; Duzenli, C; Wu, J; Moiseenko, V; Lee, R; Gill, B; Thomas, S

2014-01-01

Purpose: A system has been developed which recognizes and classifies Digital Imaging and Communication in Medicine contour data with minimal human intervention. It allows researchers to overcome obstacles which tax analysis and mining systems, including inconsistent naming conventions and differences in data age or resolution. Methods: Lexicographic and geometric analysis is used for recognition. Well-known lexicographic methods implemented include Levenshtein-Damerau, bag-of-characters, Double Metaphone, Soundex, and (word and character)-N-grams. Geometrical implementations include 3D Fourier Descriptors, probability spheres, boolean overlap, simple feature comparison (e.g. eccentricity, volume) and rule-based techniques. Both analyses implement custom, domain-specific modules (e.g. emphasis differentiating left/right organ variants). Contour labels from 60 head and neck patients are used for cross-validation. Results: Mixed-lexicographical methods show an effective improvement in more than 10% of recognition attempts compared with a pure Levenshtein-Damerau approach when withholding 70% of the lexicon. Domain-specific and geometrical techniques further boost performance. Conclusions: DICOMautomaton allows users to recognize contours semi-automatically. As usage increases and the lexicon is filled with additional structures, performance improves, increasing the overall utility of the system.

THE RECOGNITION OF SPOKEN MONO-MORPHEMIC COMPOUNDS IN CHINESE

Directory of Open Access Journals (Sweden)

Yu-da Lai

2012-12-01

Full Text Available This paper explores the auditory lexical access of mono-morphemic compounds in Chinese as a way of understanding the role of orthography in the recognition of spoken words. In traditional Chinese linguistics, a compound is a word written with two or more characters whether or not they are morphemic. A monomorphemic compound may either be a binding word, written with characters that only appear in this one word, or a non-binding word, written with characters that are chosen for their pronunciation but that also appear in other words. Our goal was to determine if this purely orthographic difference affects auditory lexical access by conducting a series of four experiments with materials matched by whole-word frequency, syllable frequency, cross-syllable predictability, cohort size, and acoustic duration, but differing in binding. An auditory lexical decision task (LDT found an orthographic effect: binding words were recognized more quickly than non-binding words. However, this effect disappeared in an auditory repetition and in a visual LDT with the same materials, implying that the orthographic effect during auditory lexical access was localized to the decision component and involved the influence of cross-character predictability without the activation of orthographic representations. This claim was further confirmed by overall faster recognition of spoken binding words in a cross-modal LDT with different types of visual interference. The theoretical and practical consequences of these findings are discussed.

Contemporary deep recurrent learning for recognition

Science.gov (United States)

Iftekharuddin, K. M.; Alam, M.; Vidyaratne, L.

2017-05-01

Large-scale feed-forward neural networks have seen intense application in many computer vision problems. However, these networks can get hefty and computationally intensive with increasing complexity of the task. Our work, for the first time in literature, introduces a Cellular Simultaneous Recurrent Network (CSRN) based hierarchical neural network for object detection. CSRN has shown to be more effective to solving complex tasks such as maze traversal and image processing when compared to generic feed forward networks. While deep neural networks (DNN) have exhibited excellent performance in object detection and recognition, such hierarchical structure has largely been absent in neural networks with recurrency. Further, our work introduces deep hierarchy in SRN for object recognition. The simultaneous recurrency results in an unfolding effect of the SRN through time, potentially enabling the design of an arbitrarily deep network. This paper shows experiments using face, facial expression and character recognition tasks using novel deep recurrent model and compares recognition performance with that of generic deep feed forward model. Finally, we demonstrate the flexibility of incorporating our proposed deep SRN based recognition framework in a humanoid robotic platform called NAO.

Automatic system for localization and recognition of vehicle plate numbers

OpenAIRE

Vázquez, N.; Nakano, M.; Pérez-Meana, H.

2003-01-01

This paper proposes a vehicle numbers plate identification system, which extracts the characters features of a plate from a captured image by a digital camera. Then identify the symbols of the number plate using a multilayer neural network. The proposed recognition system consists of two processes: The training process and the recognition process. During the training process, a database is created using 310 vehicular plate images. Then using this database a multilayer neural network is traine...

Image quality assessment for video stream recognition systems

Science.gov (United States)

Chernov, Timofey S.; Razumnuy, Nikita P.; Kozharinov, Alexander S.; Nikolaev, Dmitry P.; Arlazarov, Vladimir V.

2018-04-01

Recognition and machine vision systems have long been widely used in many disciplines to automate various processes of life and industry. Input images of optical recognition systems can be subjected to a large number of different distortions, especially in uncontrolled or natural shooting conditions, which leads to unpredictable results of recognition systems, making it impossible to assess their reliability. For this reason, it is necessary to perform quality control of the input data of recognition systems, which is facilitated by modern progress in the field of image quality evaluation. In this paper, we investigate the approach to designing optical recognition systems with built-in input image quality estimation modules and feedback, for which the necessary definitions are introduced and a model for describing such systems is constructed. The efficiency of this approach is illustrated by the example of solving the problem of selecting the best frames for recognition in a video stream for a system with limited resources. Experimental results are presented for the system for identity documents recognition, showing a significant increase in the accuracy and speed of the system under simulated conditions of automatic camera focusing, leading to blurring of frames.

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

Indian Academy of Sciences (India)

Fujisawa 2008). ... out human involvement, (ii) reading aid for the blind, (iii) automatic text entry into ... various techniques being applied for classification, and highlights the .... are fused using a simple majority voting scheme to arrive at a final decision.

Character Strengths and Academic Achievements of Undergraduate College Students of Guwahati, Assam

Directory of Open Access Journals (Sweden)

Sabiha Alam Choudhury

2017-06-01

Full Text Available Character strengths, as conceptualised by the Values-In-Action (VIA strengths classification system, are core characteristics of individuals that allow people to be virtuous (Seligman 2002. They are moral, intrinsically valuable, and ubiquitous traits that can be developed and enhanced. Social psychologists and sociologists consider achievements in college or university level, because of recognition and proper utilisation of the character strengths possessed by the individual students. The current study was conducted amongst 240 undergraduate college students of arts stream (60 males and 60 females and science stream (60 males and 60 females falling within the age group of 18-21 years, with the aim of finding out if the character strengths of the male and female undergraduate students are associated with their college academic achievements. It was found that significant correlation existed between appreciation of beauty and excellence, fairness, forgiveness, honesty, humour, kindness, love of learning and humility with the academic achievement of the students.

Recycling microcavity optical biosensors.

Science.gov (United States)

Hunt, Heather K; Armani, Andrea M

2011-04-01

Optical biosensors have tremendous potential for commercial applications in medical diagnostics, environmental monitoring, and food safety evaluation. In these applications, sensor reuse is desirable to reduce costs. To achieve this, harsh, wet chemistry treatments are required to remove surface chemistry from the sensor, typically resulting in reduced sensor performance and increased noise due to recognition moiety and optical transducer degradation. In the present work, we suggest an alternative, dry-chemistry method, based on O2 plasma treatment. This approach is compatible with typical fabrication of substrate-based optical transducers. This treatment completely removes the recognition moiety, allowing the transducer surface to be refreshed with new recognition elements and thus enabling the sensor to be recycled.

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.

A Novel Phonology- and Radical-Coded Chinese Sign Language Recognition Framework Using Accelerometer and Surface Electromyography Sensors.

Science.gov (United States)

Cheng, Juan; Chen, Xun; Liu, Aiping; Peng, Hu

2015-09-15

Sign language recognition (SLR) is an important communication tool between the deaf and the external world. It is highly necessary to develop a worldwide continuous and large-vocabulary-scale SLR system for practical usage. In this paper, we propose a novel phonology- and radical-coded Chinese SLR framework to demonstrate the feasibility of continuous SLR using accelerometer (ACC) and surface electromyography (sEMG) sensors. The continuous Chinese characters, consisting of coded sign gestures, are first segmented into active segments using EMG signals by means of moving average algorithm. Then, features of each component are extracted from both ACC and sEMG signals of active segments (i.e., palm orientation represented by the mean and variance of ACC signals, hand movement represented by the fixed-point ACC sequence, and hand shape represented by both the mean absolute value (MAV) and autoregressive model coefficients (ARs)). Afterwards, palm orientation is first classified, distinguishing "Palm Downward" sign gestures from "Palm Inward" ones. Only the "Palm Inward" gestures are sent for further hand movement and hand shape recognition by dynamic time warping (DTW) algorithm and hidden Markov models (HMM) respectively. Finally, component recognition results are integrated to identify one certain coded gesture. Experimental results demonstrate that the proposed SLR framework with a vocabulary scale of 223 characters can achieve an averaged recognition accuracy of 96.01% ± 0.83% for coded gesture recognition tasks and 92.73% ± 1.47% for character recognition tasks. Besides, it demonstrats that sEMG signals are rather consistent for a given hand shape independent of hand movements. Hence, the number of training samples will not be significantly increased when the vocabulary scale increases, since not only the number of the completely new proposed coded gestures is constant and limited, but also the transition movement which connects successive signs needs no

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.

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

Pattern recognition and modelling of earthquake registrations with interactive computer support

International Nuclear Information System (INIS)

Manova, Katarina S.

2004-01-01

The object of the thesis is Pattern Recognition. Pattern recognition i.e. classification, is applied in many fields: speech recognition, hand printed character recognition, medical analysis, satellite and aerial-photo interpretations, biology, computer vision, information retrieval and so on. In this thesis is studied its applicability in seismology. Signal classification is an area of great importance in a wide variety of applications. This thesis deals with the problem of (automatic) classification of earthquake signals, which are non-stationary signals. Non-stationary signal classification is an area of active research in the signal and image processing community. The goal of the thesis is recognition of earthquake signals according to their epicentral zone. Source classification i.e. recognition is based on transformation of seismograms (earthquake registrations) to images, via time-frequency transformations, and applying image processing and pattern recognition techniques for feature extraction, classification and recognition. The tested data include local earthquakes from seismic regions in Macedonia. By using actual seismic data it is shown that proposed methods provide satisfactory results for classification and recognition.(Author)

Action Recognition by Joint Spatial-Temporal Motion Feature

Directory of Open Access Journals (Sweden)

Weihua Zhang

2013-01-01

Full Text Available This paper introduces a method for human action recognition based on optical flow motion features extraction. Automatic spatial and temporal alignments are combined together in order to encourage the temporal consistence on each action by an enhanced dynamic time warping (DTW algorithm. At the same time, a fast method based on coarse-to-fine DTW constraint to improve computational performance without reducing accuracy is induced. The main contributions of this study include (1 a joint spatial-temporal multiresolution optical flow computation method which can keep encoding more informative motion information than recent proposed methods, (2 an enhanced DTW method to improve temporal consistence of motion in action recognition, and (3 coarse-to-fine DTW constraint on motion features pyramids to speed up recognition performance. Using this method, high recognition accuracy is achieved on different action databases like Weizmann database and KTH database.

Food brand recognition and BMI in preschoolers.

Science.gov (United States)

Harrison, Kristen; Moorman, Jessica; Peralta, Mericarmen; Fayhee, Kally

2017-07-01

Children's food brand recognition predicts health-related outcomes such as preference for obesogenic foods and increased risk for overweight. However, it is uncertain to what degree food brand recognition acts as a proxy for other factors such as parental education and income, child vocabulary, child age, child race/ethnicity, parent healthy eating guidance, child commercial TV viewing, and child dietary intake, all of which may influence or be influenced by food brand recognition. U.S. preschoolers (N = 247, average age 56 months) were measured for BMI and completed the Peabody Picture Vocabulary Test plus recognition and recall measures for a selection of U.S. food brands. Parents completed measures of healthy eating guidance, child dietary intake, child commercial TV viewing, parent education, household income, parent BMI, and child age and race/ethnicity. Controlling these variables, child food brand recognition predicted higher child BMI percentile. Further, qualitative examination of children's incorrect answers to recall items demonstrated perceptual confusion between brand mascots and other fantasy characters to which children are exposed during the preschool years, extending theory on child consumer development. Copyright © 2017 Elsevier Ltd. All rights reserved.

Adversity, emotion recognition, and empathic concern in high-risk youth.

Directory of Open Access Journals (Sweden)

Jodi A Quas

Full Text Available Little is known about how emotion recognition and empathy jointly operate in youth growing up in contexts defined by persistent adversity. We investigated whether adversity exposure in two groups of youth was associated with reduced empathy and whether deficits in emotion recognition mediated this association. Foster, rural poor, and comparison youth from Swaziland, Africa identified emotional expressions and rated their empathic concern for characters depicted in images showing positive, ambiguous, and negative scenes. Rural and foster youth perceived greater anger and happiness in the main characters in ambiguous and negative images than did comparison youth. Rural children also perceived less sadness. Youth's perceptions of sadness in the negative and ambiguous expressions mediated the relation between adversity and empathic concern, but only for the rural youth, who perceived less sadness, which then predicted less empathy. Findings provide new insight into processes that underlie empathic tendencies in adversity-exposed youth and highlight potential directions for interventions to increase empathy.

Container-code recognition system based on computer vision and deep neural networks

Science.gov (United States)

Liu, Yi; Li, Tianjian; Jiang, Li; Liang, Xiaoyao

2018-04-01

Automatic container-code recognition system becomes a crucial requirement for ship transportation industry in recent years. In this paper, an automatic container-code recognition system based on computer vision and deep neural networks is proposed. The system consists of two modules, detection module and recognition module. The detection module applies both algorithms based on computer vision and neural networks, and generates a better detection result through combination to avoid the drawbacks of the two methods. The combined detection results are also collected for online training of the neural networks. The recognition module exploits both character segmentation and end-to-end recognition, and outputs the recognition result which passes the verification. When the recognition module generates false recognition, the result will be corrected and collected for online training of the end-to-end recognition sub-module. By combining several algorithms, the system is able to deal with more situations, and the online training mechanism can improve the performance of the neural networks at runtime. The proposed system is able to achieve 93% of overall recognition accuracy.

Photonics: From target recognition to lesion detection

Science.gov (United States)

Henry, E. Michael

1994-01-01

Since 1989, Martin Marietta has invested in the development of an innovative concept for robust real-time pattern recognition for any two-dimensioanal sensor. This concept has been tested in simulation, and in laboratory and field hardware, for a number of DOD and commercial uses from automatic target recognition to manufacturing inspection. We have now joined Rose Health Care Systems in developing its use for medical diagnostics. The concept is based on determining regions of interest by using optical Fourier bandpassing as a scene segmentation technique, enhancing those regions using wavelet filters, passing the enhanced regions to a neural network for analysis and initial pattern identification, and following this initial identification with confirmation by optical correlation. The optical scene segmentation and pattern confirmation are performed by the same optical module. The neural network is a recursive error minimization network with a small number of connections and nodes that rapidly converges to a global minimum.

Probabilistic Structured Query Methods

National Research Council Canada - National Science Library

Darwish, Kareem; Oard, Douglas W

2003-01-01

.... Statistically significant improvements in retrieval effectiveness are demonstrated for cross-language retrieval and for retrieval based on optical character recognition when replacement probabilities...

Optical properties of marine waters and the development of bio-optical algorithms

Digital Repository Service at National Institute of Oceanography (India)

Desa, E.

This paper presents the primary optical variables used in the measurement of the optical properties of marine waters. How can in-situ measurements be used in the optical recognition of coastal and open ocean waters. We then look at bio...

An Investigation of the Compensatory Effectiveness of Assistive Technology on Postsecondary Students with Learning Disabilities. Final Report.

Science.gov (United States)

Murphy, Harry; Higgins, Eleanor

This final report describes the activities and accomplishments of a 3-year study on the compensatory effectiveness of three assistive technologies, optical character recognition, speech synthesis, and speech recognition, on postsecondary students (N=140) with learning disabilities. These technologies were investigated relative to: (1) immediate…

Automatic Recognition of Chinese Personal Name Using Conditional Random Fields and Knowledge Base

Directory of Open Access Journals (Sweden)

Chuan Gu

2015-01-01

Full Text Available According to the features of Chinese personal name, we present an approach for Chinese personal name recognition based on conditional random fields (CRF and knowledge base in this paper. The method builds multiple features of CRF model by adopting Chinese character as processing unit, selects useful features based on selection algorithm of knowledge base and incremental feature template, and finally implements the automatic recognition of Chinese personal name from Chinese document. The experimental results on open real corpus demonstrated the effectiveness of our method and obtained high accuracy rate and high recall rate of recognition.

Recognition and cinema: new ways of approaching

Directory of Open Access Journals (Sweden)

José Luis GARCÍA MARTÍNEZ

2016-09-01

Full Text Available Along the following lines we propose the use of films for educational purposes. Our main argument, based on philosophical grounds, shows the use of film format to emphasize and understand people’s motivations and actions. The reflections brought about by empathy with the characters are the first step in the approach of the topic of recognition, a term that in the medical framework involves taking into account the various aspects of inter-human relationships. Recognition of “the other” as he/she stands, implies addressing differences and providing a better doctor-patient relationship. The analysis of several films might encourage the acknowledgement of recognition as one of the key concepts to understand our ways of relating within plural societies with different lifestyles and different outlooks on the world. We believe that the effort made in dealing with such topics results in greater closeness to the patient and, therefore, better care.

Analysis of contour images using optics of spiral beams

Science.gov (United States)

Volostnikov, V. G.; Kishkin, S. A.; Kotova, S. P.

2018-03-01

An approach is outlined to the recognition of contour images using computer technology based on coherent optics principles. A mathematical description of the recognition process algorithm and the results of numerical modelling are presented. The developed approach to the recognition of contour images using optics of spiral beams is described and justified.

Character animation fundamentals developing skills for 2D and 3D character animation

CERN Document Server

Roberts, Steve

2012-01-01

Expand your animation toolkit and remain competitive in the industry with this leading resource for 2D and 3D character animation techniques. Apply the industry's best practices to your own workflows and develop 2D, 3D and hybrid characters with ease. With side by side comparisons of 2D and 3D character design, improve your character animation and master traditional principles and processes including weight and balance, timing and walks. Develop characters inspired by humans, birds, fish, snakes and four legged animals. Breathe life into your character and develop a characters personality w

Rapid extraction of lexical tone phonology in Chinese characters: a visual mismatch negativity study.

Directory of Open Access Journals (Sweden)

Xiao-Dong Wang

Full Text Available BACKGROUND: In alphabetic languages, emerging evidence from behavioral and neuroimaging studies shows the rapid and automatic activation of phonological information in visual word recognition. In the mapping from orthography to phonology, unlike most alphabetic languages in which there is a natural correspondence between the visual and phonological forms, in logographic Chinese, the mapping between visual and phonological forms is rather arbitrary and depends on learning and experience. The issue of whether the phonological information is rapidly and automatically extracted in Chinese characters by the brain has not yet been thoroughly addressed. METHODOLOGY/PRINCIPAL FINDINGS: We continuously presented Chinese characters differing in orthography and meaning to adult native Mandarin Chinese speakers to construct a constant varying visual stream. In the stream, most stimuli were homophones of Chinese characters: The phonological features embedded in these visual characters were the same, including consonants, vowels and the lexical tone. Occasionally, the rule of phonology was randomly violated by characters whose phonological features differed in the lexical tone. CONCLUSIONS/SIGNIFICANCE: We showed that the violation of the lexical tone phonology evoked an early, robust visual response, as revealed by whole-head electrical recordings of the visual mismatch negativity (vMMN, indicating the rapid extraction of phonological information embedded in Chinese characters. Source analysis revealed that the vMMN was involved in neural activations of the visual cortex, suggesting that the visual sensory memory is sensitive to phonological information embedded in visual words at an early processing stage.

Rapid extraction of lexical tone phonology in Chinese characters: a visual mismatch negativity study.

Science.gov (United States)

Wang, Xiao-Dong; Liu, A-Ping; Wu, Yin-Yuan; Wang, Peng

2013-01-01

In alphabetic languages, emerging evidence from behavioral and neuroimaging studies shows the rapid and automatic activation of phonological information in visual word recognition. In the mapping from orthography to phonology, unlike most alphabetic languages in which there is a natural correspondence between the visual and phonological forms, in logographic Chinese, the mapping between visual and phonological forms is rather arbitrary and depends on learning and experience. The issue of whether the phonological information is rapidly and automatically extracted in Chinese characters by the brain has not yet been thoroughly addressed. We continuously presented Chinese characters differing in orthography and meaning to adult native Mandarin Chinese speakers to construct a constant varying visual stream. In the stream, most stimuli were homophones of Chinese characters: The phonological features embedded in these visual characters were the same, including consonants, vowels and the lexical tone. Occasionally, the rule of phonology was randomly violated by characters whose phonological features differed in the lexical tone. We showed that the violation of the lexical tone phonology evoked an early, robust visual response, as revealed by whole-head electrical recordings of the visual mismatch negativity (vMMN), indicating the rapid extraction of phonological information embedded in Chinese characters. Source analysis revealed that the vMMN was involved in neural activations of the visual cortex, suggesting that the visual sensory memory is sensitive to phonological information embedded in visual words at an early processing stage.

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.

Neural network application for thermal image recognition of low-resolution objects

Science.gov (United States)

Fang, Yi-Chin; Wu, Bo-Wen

2007-02-01

In the ever-changing situation on a battle field, accurate recognition of a distant object is critical to a commander's decision-making and the general public's safety. Efficiently distinguishing between an enemy's armoured vehicles and ordinary civilian houses under all weather conditions has become an important research topic. This study presents a system for recognizing an armoured vehicle by distinguishing marks and contours. The characteristics of 12 different shapes and 12 characters are used to explore thermal image recognition under the circumstance of long distance and low resolution. Although the recognition capability of human eyes is superior to that of artificial intelligence under normal conditions, it tends to deteriorate substantially under long-distance and low-resolution scenarios. This study presents an effective method for choosing features and processing images. The artificial neural network technique is applied to further improve the probability of accurate recognition well beyond the limit of the recognition capability of human eyes.

End-to-End Neural Optical Music Recognition of Monophonic Scores

Directory of Open Access Journals (Sweden)

Jorge Calvo-Zaragoza

2018-04-01

Full Text Available Optical Music Recognition is a field of research that investigates how to computationally decode music notation from images. Despite the efforts made so far, there are hardly any complete solutions to the problem. In this work, we study the use of neural networks that work in an end-to-end manner. This is achieved by using a neural model that combines the capabilities of convolutional neural networks, which work on the input image, and recurrent neural networks, which deal with the sequential nature of the problem. Thanks to the use of the the so-called Connectionist Temporal Classification loss function, these models can be directly trained from input images accompanied by their corresponding transcripts into music symbol sequences. We also present the Printed Music Scores dataset, containing more than 80,000 monodic single-staff real scores in common western notation, that is used to train and evaluate the neural approach. In our experiments, it is demonstrated that this formulation can be carried out successfully. Additionally, we study several considerations about the codification of the output musical sequences, the convergence and scalability of the neural models, as well as the ability of this approach to locate symbols in the input score.

Chinese handwriting recognition an algorithmic perspective

CERN Document Server

Su, Tonghua

2013-01-01

This book provides an algorithmic perspective on the recent development of Chinese handwriting recognition. Two technically sound strategies, the segmentation-free and integrated segmentation-recognition strategy, are investigated and algorithms that have worked well in practice are primarily focused on. Baseline systems are initially presented for these strategies and are subsequently expanded on and incrementally improved. The sophisticated algorithms covered include: 1) string sample expansion algorithms which synthesize string samples from isolated characters or distort realistic string samples; 2) enhanced feature representation algorithms, e.g. enhanced four-plane features and Delta features; 3) novel learning algorithms, such as Perceptron learning with dynamic margin, MPE training and distributed training; and lastly 4) ensemble algorithms, that is, combining the two strategies using both parallel structure and serial structure. All the while, the book moves from basic to advanced algorithms, helping ...

Object Attention Patches for Text Detection and Recognition in Scene Images using SIFT

NARCIS (Netherlands)

Sriman, Bowornrat; Schomaker, Lambertus; De Marsico, Maria; Figueiredo, Mário; Fred, Ana

2015-01-01

Natural urban scene images contain many problems for character recognition such as luminance noise, varying font styles or cluttered backgrounds. Detecting and recognizing text in a natural scene is a difficult problem. Several techniques have been proposed to overcome these problems. These are,

Multi-digit handwritten sindhi numerals recognition using som neural network

International Nuclear Information System (INIS)

Chandio, A.A.; Jalbani, A.H.; Awan, S.A.

2017-01-01

In this research paper a multi-digit Sindhi handwritten numerals recognition system using SOM Neural Network is presented. Handwritten digits recognition is one of the challenging tasks and a lot of research is being carried out since many years. A remarkable work has been done for recognition of isolated handwritten characters as well as digits in many languages like English, Arabic, Devanagari, Chinese, Urdu and Pashto. However, the literature reviewed does not show any remarkable work done for Sindhi numerals recognition. The recognition of Sindhi digits is a difficult task due to the various writing styles and different font sizes. Therefore, SOM (Self-Organizing Map), a NN (Neural Network) method is used which can recognize digits with various writing styles and different font sizes. Only one sample is required to train the network for each pair of multi-digit numerals. A database consisting of 4000 samples of multi-digits consisting only two digits from 10-50 and other matching numerals have been collected by 50 users and the experimental results of proposed method show that an accuracy of 86.89% is achieved. (author)

Is Syntactic-Category Processing Obligatory in Visual Word Recognition? Evidence from Chinese

Science.gov (United States)

Wong, Andus Wing-Kuen; Chen, Hsuan-Chih

2012-01-01

Three experiments were conducted to investigate how syntactic-category and semantic information is processed in visual word recognition. The stimuli were two-character Chinese words in which semantic and syntactic-category ambiguities were factorially manipulated. A lexical decision task was employed in Experiment 1, whereas a semantic relatedness…

Parsing and Tagging of Binlingual Dictionary

National Research Council Canada - National Science Library

Ma, Huanfeng; Karagol-Ayan, Burcu; Doermann, David S; Oard, Doug; Wang, Jianqiang

2003-01-01

Bilingual dictionaries hold great potential as a source of lexical resources for training and testing automated systems for optical character recognition, machine translation, and cross-language information retrieval...

Parsing and Tagging of Bilingual Dictionary

National Research Council Canada - National Science Library

Ma, Huanfeng; Karagol-Ayan, Burcu; Doermann, David S; Oard, Doug; Wang, Jianqiang

2003-01-01

Bilingual dictionaries hold great potential as a source of lexical resources for training and testing automated systems for optical character recognition, machine translation, and cross-language information retrieval...

Paired Model Evaluation of OCR Algorithms

National Research Council Canada - National Science Library

Kanungo, Tapas; Marton, Gregory A; Bulbul, Osama

1998-01-01

Characterizing the performance of Optical Character Recognition (OCR) systems is crucial for monitoring technical progress predicting, OCR performance, providing scientific explanations for system behavior and identifying open problems...

A semantics of love: Brief notes on desire and recognition in Georges Bataille

Directory of Open Access Journals (Sweden)

Herivelto Pereira de Souza

2013-06-01

Full Text Available According to the Hegelian scheme re-proposed by Honneth, the first pattern of intersubjective recognition, still below the juridical mediation, is the sphere of interactions marked by affective bonds, or love. It is considered a first stage mostly because recognition is rooted in the partners' mutual dependency as needy creatures, which demand care and the emotional approval that follows it. In this sense, a constitutional lacking emerges as the fundamental character of the most primitive kinds of interaction embedded in social norms. And that is important inasmuch the other stages of recognitive practices depend on this first one, in which subjects acquire capacities for rational and moral reasoning and action in the public sphere. However, one could question to what extent the same normative structure can be taking as underlying every loving relationship, as oriented by an affirmation of the subject's independence, while presupposing involuntary feelings of liking and attraction. After all, if the aspirations of reciprocal recognition in this realm are intrinsically related to very concrete features, why taking child caring, friendship and sexual encounter as referred to the same set of recognition patterns? If Honneth's recourse to psychoanalytic theory makes it clear why in all these kinds of interaction is to be found erotic contents of libidinal character, on the other hand one gets no clue on why the very different forms of satisfaction of the drives do not come into consideration. At this point it seems important to recall Georges Bataille's account of sexuality to think not only about the limits of recognition, but also its dialectical structure. The central notion of transgression helps understand why the normative grounds of intersubjective acknowledgment regarding at least some love relationships require a sort of suspension which is not the mere suppression of their validity: the violence that resides at the core of such erotic

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.

Development of real-time motion capture system for 3D on-line games linked with virtual character

Science.gov (United States)

Kim, Jong Hyeong; Ryu, Young Kee; Cho, Hyung Suck

2004-10-01

Motion tracking method is being issued as essential part of the entertainment, medical, sports, education and industry with the development of 3-D virtual reality. Virtual human character in the digital animation and game application has been controlled by interfacing devices; mouse, joysticks, midi-slider, and so on. Those devices could not enable virtual human character to move smoothly and naturally. Furthermore, high-end human motion capture systems in commercial market are expensive and complicated. In this paper, we proposed a practical and fast motion capturing system consisting of optic sensors, and linked the data with 3-D game character with real time. The prototype experiment setup is successfully applied to a boxing game which requires very fast movement of human character.

Recognition Number of The Vehicle Plate Using Otsu Method and K-Nearest Neighbour Classification

Directory of Open Access Journals (Sweden)

Maulidia Rahmah Hidayah

2017-05-01

Full Text Available The current topic that is interesting as a solution of the impact of public service improvement toward vehicle is License Plate Recognition (LPR, but it still needs to develop the research of LPR method. Some of the previous researchs showed that K-Nearest Neighbour (KNN succeed in car license plate recognition. The Objectives of this research was to determine the implementation and accuracy of Otsu Method toward license plate recognition. The method of this research was Otsu method to extract the characteristics and image of the plate into binary image and KNN as recognition classification method of each character. The development of the license plate recognition program by using Otsu method and classification of KNN is following the steps of pattern recognition, such as input and sensing, pre-processing, extraction feature Otsu method binary, segmentation, KNN classification method and post-processing by calculating the level of accuracy. The study showed that this program can recognize by 82% from 100 test plate with 93,75% of number recognition accuracy and 91,92% of letter recognition accuracy. 

Recognition of Time Stamps on Full-Disk Hα Images Using Machine Learning Methods

Science.gov (United States)

Xu, Y.; Huang, N.; Jing, J.; Liu, C.; Wang, H.; Fu, G.

2016-12-01

Observation and understanding of the physics of the 11-year solar activity cycle and 22-year magnetic cycle are among the most important research topics in solar physics. The solar cycle is responsible for magnetic field and particle fluctuation in the near-earth environment that have been found increasingly important in affecting the living of human beings in the modern era. A systematic study of large-scale solar activities, as made possible by our rich data archive, will further help us to understand the global-scale magnetic fields that are closely related to solar cycles. The long-time-span data archive includes both full-disk and high-resolution Hα images. Prior to the widely use of CCD cameras in 1990s, 35-mm films were the major media to store images. The research group at NJIT recently finished the digitization of film data obtained by the National Solar Observatory (NSO) and Big Bear Solar Observatory (BBSO) covering the period of 1953 to 2000. The total volume of data exceeds 60 TB. To make this huge database scientific valuable, some processing and calibration are required. One of the most important steps is to read the time stamps on all of the 14 million images, which is almost impossible to be done manually. We implemented three different methods to recognize the time stamps automatically, including Optical Character Recognition (OCR), Classification Tree and TensorFlow. The latter two are known as machine learning algorithms which are very popular now a day in pattern recognition area. We will present some sample images and the results of clock recognition from all three methods.

Sadhana | Indian Academy of Sciences

Indian Academy of Sciences (India)

Home; Journals; Sadhana. M Mitra. Articles written in Sadhana. Volume 27 Issue 1 February 2002 pp 23-34. Automatic recognition of printed Oriya script · B B Chaudhuri U Pal M Mitra · More Details Abstract Fulltext PDF. This paper deals with an Optical Character Recognition (OCR) system for printed Oriya script.

A Horizontal Tilt Correction Method for Ship License Numbers Recognition

Science.gov (United States)

Liu, Baolong; Zhang, Sanyuan; Hong, Zhenjie; Ye, Xiuzi

2018-02-01

An automatic ship license numbers (SLNs) recognition system plays a significant role in intelligent waterway transportation systems since it can be used to identify ships by recognizing the characters in SLNs. Tilt occurs frequently in many SLNs because the monitors and the ships usually have great vertical or horizontal angles, which decreases the accuracy and robustness of a SLNs recognition system significantly. In this paper, we present a horizontal tilt correction method for SLNs. For an input tilt SLN image, the proposed method accomplishes the correction task through three main steps. First, a MSER-based characters’ center-points computation algorithm is designed to compute the accurate center-points of the characters contained in the input SLN image. Second, a L 1- L 2 distance-based straight line is fitted to the computed center-points using M-estimator algorithm. The tilt angle is estimated at this stage. Finally, based on the computed tilt angle, an affine transformation rotation is conducted to rotate and to correct the input SLN horizontally. At last, the proposed method is tested on 200 tilt SLN images, the proposed method is proved to be effective with a tilt correction rate of 80.5%.

Neighborhood Frequency Effect in Chinese Word Recognition: Evidence from Naming and Lexical Decision

Science.gov (United States)

Li, Meng-Feng; Gao, Xin-Yu; Chou, Tai-Li; Wu, Jei-Tun

2017-01-01

Neighborhood frequency is a crucial variable to know the nature of word recognition. Different from alphabetic scripts, neighborhood frequency in Chinese is usually confounded by component character frequency and neighborhood size. Three experiments were designed to explore the role of the neighborhood frequency effect in Chinese and the stimuli…

Optical computing.

Science.gov (United States)

Stroke, G. W.

1972-01-01

Applications of the optical computer include an approach for increasing the sharpness of images obtained from the most powerful electron microscopes and fingerprint/credit card identification. The information-handling capability of the various optical computing processes is very great. Modern synthetic-aperture radars scan upward of 100,000 resolvable elements per second. Fields which have assumed major importance on the basis of optical computing principles are optical image deblurring, coherent side-looking synthetic-aperture radar, and correlative pattern recognition. Some examples of the most dramatic image deblurring results are shown.

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...

Recognition in Programmes for Children with Special Needs

Directory of Open Access Journals (Sweden)

Marjeta Šmid

2016-09-01

Full Text Available The purpose of this article is to examine the factors that affect the inclusion of pupils in programmes for children with special needs from the perspective of the theory of recognition. The concept of recognition, which includes three aspects of social justice (economic, cultural and political, argues that the institutional arrangements that prevent ‘parity of participation’ in the school social life of the children with special needs are affected not only by economic distribution but also by the patterns of cultural values. A review of the literature shows that the arrangements of education of children with special needs are influenced primarily by the patterns of cultural values of capability and inferiority, as well as stereotypical images of children with special needs. Due to the significant emphasis on learning skills for academic knowledge and grades, less attention is dedicated to factors of recognition and representational character, making it impossible to improve some meaningful elements of inclusion. Any participation of pupils in activities, the voices of the children, visibility of the children due to achievements and the problems of arbitrariness in determining boundaries between programmes are some such elements. Moreover, aided by theories, the actions that could contribute to better inclusion are reviewed. An effective approach to changes would be the creation of transformative conditions for the recognition and balancing of redistribution, recognition, and representation.

Research on Recognition and Evaluation of Traffic Guide Sign

OpenAIRE

Li Yuan; Ming-jie Cai; Tang-yi Guo; Yu Jiang

2015-01-01

Traffic guide signs are effective only when they are clearly recognized by drivers. Three experiments were conducted in this study. In the first, the influence factors of guide sign recognition were studied. This study investigated 11 main factors with a convenience sample of drivers from Nanjing city in China. Weights of different influence factors were obtained through analytic hierarchy process (AHP). The results showed that the setting position, occlusion degree, and character size of gui...

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

International Nuclear Information System (INIS)

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

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 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. (paper)

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.

76 FR 2309 - Consumer Information Regulations; Fees for Use of Traction Skid Pads

Science.gov (United States)

2011-01-13

... require motor vehicle and tire manufacturers and tire brand owners to label such tires with information... submissions.\\4\\ \\4\\ Optical character recognition (OCR) is the process of converting an image of text, such as...

Throwing Down the Visual Intelligence Gauntlet

KAUST Repository

Tan, Cheston; Leibo, Joel Z.; Poggio, Tomaso

2013-01-01

In recent years, scientific and technological advances have produced artificial systems that have matched or surpassed human capabilities in narrow domains such as face detection and optical character recognition. However, the problem of producing

An audiovisual emotion recognition system

Science.gov (United States)

Han, Yi; Wang, Guoyin; Yang, Yong; He, Kun

2007-12-01

Human emotions could be expressed by many bio-symbols. Speech and facial expression are two of them. They are both regarded as emotional information which is playing an important role in human-computer interaction. Based on our previous studies on emotion recognition, an audiovisual emotion recognition system is developed and represented in this paper. The system is designed for real-time practice, and is guaranteed by some integrated modules. These modules include speech enhancement for eliminating noises, rapid face detection for locating face from background image, example based shape learning for facial feature alignment, and optical flow based tracking algorithm for facial feature tracking. It is known that irrelevant features and high dimensionality of the data can hurt the performance of classifier. Rough set-based feature selection is a good method for dimension reduction. So 13 speech features out of 37 ones and 10 facial features out of 33 ones are selected to represent emotional information, and 52 audiovisual features are selected due to the synchronization when speech and video fused together. The experiment results have demonstrated that this system performs well in real-time practice and has high recognition rate. Our results also show that the work in multimodules fused recognition will become the trend of emotion recognition in the future.

Mobile based optical form evaluation system

Directory of Open Access Journals (Sweden)

Asım Sinan YÜKSEL

2016-05-01

Full Text Available Optical forms that contain multiple-choice answers are widely used both for electing students and evaluating student achievements in education systems in our country and worldwide. Optical forms are evaluated by employing optical mark recognition techniques through optical readers. High cost of these machines, limited access to them, long waiting time for evaluation results make the process hard for educationists working in cities or countries. In this study, a mobile application was developed for the educationists who own mobile phones or tablets for the purpose of evaluating students' answer sheets quickly and independent of location and optical readers. Optical form recognition, reading and evaluation processes are done on the image of student's answer sheet that is taken with the mobile phone or tablet of educationist. The Android based mobile application that we developed has a user-friendly interface, high success rate and is the first of our knowledge application that operates on mobile platforms in this field.

Developing Character and Values for Global Citizens: Analysis of pre-service science teachers' moral reasoning on socioscientific issues

Science.gov (United States)

Lee, Hyunju; Chang, Hyunsook; Choi, Kyunghee; Kim, Sung-Won; Zeidler, Dana L.

2012-04-01

Character and values are the essential driving forces that serve as general guides or points of reference for individuals to support decision-making and to act responsibly about global socioscientific issues (SSIs). Based on this assumption, we investigated to what extent pre-service science teachers (PSTs) of South Korea possess character and values as global citizens; these values include ecological worldview, socioscientific accountability, and social and moral compassion. Eighteen PSTs participated in the SSI programs focusing on developing character and values through dialogical and reflective processes. SSIs were centered on the use of nuclear power generation, climate change, and embryonic stem cell research. The results indicated that PSTs showed three key elements of character and values, but failed to apply consistent moral principles on the issues and demonstrated limited global perspectives. While they tended to approach the issues with emotion and sympathy, they nonetheless failed to perceive themselves as major moral agents who are able to actively resolve large-scale societal issues. This study also suggests that the SSI programs can facilitate socioscientific reasoning to include abilities such as recognition of the complexity of SSIs, examine issues from multiple perspectives, and exhibit skepticism about information.

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. Copyright © 2015 Elsevier B.V. All rights reserved.

Character Apps for Children's Snacks: Effects of Character Awareness on Snack Selection and Consumption Patterns.

Science.gov (United States)

Putnam, Marisa M; Cotto, Caroline E; Calvert, Sandra L

2018-04-01

Media characters are used to market snacks that are typically of poor nutritional value, which has been linked to childhood obesity. This study examines whether children's snack selections and consumption patterns are influenced by an app depicting a popular children's media character, as well as the role that children's awareness of the character plays. The results can increase our understanding of how to encourage healthier snack selection and consumption in newer game-based marketing venues, such as apps. Four- and 5-year-old children (N = 132) played a bowling game on an iPad with no character or with a character holding either healthier or unhealthy snacks. After app-play, children selected and consumed healthier or unhealthy snacks. Children's awareness of the character was measured by children's verbalizations of the character's name during or after app-play. An ordered logistic regression found no significant effect of treatment conditions compared with the control group. Within treatment conditions, awareness of the character led to selection and consumption of more healthy snacks in the healthier condition (odds ratio β = 10.340, P = 0.008), and of unhealthy snacks in the unhealthy condition (odds ratio β = 0.228, P = 0.033), but children were unaware that the character influenced their decisions. Results suggest that young children will choose and consume healthier, not just unhealthy, products when they are aware that a popular character in an app is associated with the snack, potentially leading to healthier eating patterns.

A Missing Piece of the Contemporary Character Education Puzzle: The Individualisation of Moral Character

Science.gov (United States)

Chen, Yi-Lin

2013-01-01

The different sorts of virtuous people who display various virtues to a remarkable degree have brought the issue of individualisation of moral character to the forefront. It signals a more personal dimension of character development which is notoriously ignored in the current discourse on character education. The case is made that since in…

Character Issues: Reality Character Problems and Solutions through Education in Indonesia

Science.gov (United States)

Saidek, Abdul Rahim; Islami, Raisul; Abdoludin

2016-01-01

Weak character education raises the problem of corruption, a fight between students, free sex, drugs and rape/abortion indicate that the issue of character education of the nation must be improved and the concern of all parties, the nation's leaders, law enforcement officers, educators, religious leaders, groups and other etc. There are two…

Effects of licensed characters on children's taste and snack preferences in Guatemala, a low/middle income country.

Science.gov (United States)

Letona, P; Chacon, V; Roberto, C; Barnoya, J

2014-11-01

Marketing of high-energy, low-nutrient foods is one of the contributing factors to the obesity-promoting environment. Licensed characters are typically used to market these foods to children because they increase brand recognition and sales, and data suggest that they affect the taste and snack preferences of children in high-income countries, but it has not yet been explored in low/middle income countries (LMICs). We sought to examine how licensed characters on food packaging influence children's taste and snack preferences in Guatemala, a LMIC. One hundred twenty-one children (mean ± s.d. age, 7.4 ± 1.9 years) from four (two preschool and two elementary) public schools in Guatemala tasted three food types: potato chips, crackers and carrots. Each was presented in two identical packages, except that one had a licensed character and the other did not. Children tasted the foods (six total) in each package and answered whether they tasted the same or one tasted better. Snack preference was also evaluated. Children were significantly (Pstrategy.

A Development of a System Enables Character Input and PC Operation via Voice for a Physically Disabled Person with a Speech Impediment

Science.gov (United States)

Tanioka, Toshimasa; Egashira, Hiroyuki; Takata, Mayumi; Okazaki, Yasuhisa; Watanabe, Kenzi; Kondo, Hiroki

We have designed and implemented a PC operation support system for a physically disabled person with a speech impediment via voice. Voice operation is an effective method for a physically disabled person with involuntary movement of the limbs and the head. We have applied a commercial speech recognition engine to develop our system for practical purposes. Adoption of a commercial engine reduces development cost and will contribute to make our system useful to another speech impediment people. We have customized commercial speech recognition engine so that it can recognize the utterance of a person with a speech impediment. We have restricted the words that the recognition engine recognizes and separated a target words from similar words in pronunciation to avoid misrecognition. Huge number of words registered in commercial speech recognition engines cause frequent misrecognition for speech impediments' utterance, because their utterance is not clear and unstable. We have solved this problem by narrowing the choice of input down in a small number and also by registering their ambiguous pronunciations in addition to the original ones. To realize all character inputs and all PC operation with a small number of words, we have designed multiple input modes with categorized dictionaries and have introduced two-step input in each mode except numeral input to enable correct operation with small number of words. The system we have developed is in practical level. The first author of this paper is physically disabled with a speech impediment. He has been able not only character input into PC but also to operate Windows system smoothly by using this system. He uses this system in his daily life. This paper is written by him with this system. At present, the speech recognition is customized to him. It is, however, possible to customize for other users by changing words and registering new pronunciation according to each user's utterance.

Quantum formulation for nanoscale optical and material chirality: symmetry issues, space and time parity, and observables

Science.gov (United States)

Andrews, D. L.

2018-03-01

To properly represent the interplay and coupling of optical and material chirality at the photon-molecule or photon-nanoparticle level invites a recognition of quantum facets in the fundamental aspects and mechanisms of light-matter interaction. It is therefore appropriate to cast theory in a general quantum form, one that is applicable to both linear and nonlinear optics as well as various forms of chiroptical interaction including chiral optomechanics. Such a framework, fully accounting for both radiation and matter in quantum terms, facilitates the scrutiny and identification of key issues concerning spatial and temporal parity, scale, dissipation and measurement. Furthermore it fully provides for describing the interactions of structured or twisted light beams with a vortex character, and it leads to the complete identification of symmetry conditions for materials to provide for chiral discrimination. Quantum considerations also lend a distinctive perspective to the very different senses in which other aspects of chirality are recognized in metamaterials. Duly attending to the symmetry principles governing allowed or disallowed forms of chiral discrimination supports an objective appraisal of the experimental possibilities and developing applications.

Towards Tetraradicaloid: The Effect of Fusion Mode on Radical Character and Chemical Reactivity

KAUST Repository

Hu, Pan

2015-12-30

Open-shell singlet diradicaloids display unique electronic, non-linear optical and magnetic activity and could become novel molecular materials for organic electronics, photonics and spintronics. However, design and synthesis of diradicaloids with a significant polyradical character is a challenging task for chemists. In this article, we report our efforts toward tetraradicaloid system. A series of potential tetraradicaloids by fusion of two p-quinodimethane (p-QDM) units with naphthalene or benzene rings in different modes were synthesized. Their model compounds containing one p-QDM moiety were also prepared and compared. Their ground-state structures, physical properties and chemical reactivity were systematically investigated by various exper-imental methods such as steady-state and transient absorption, two-photon absorption, X-ray crystallographic analysis, electron spin resonance, superconducting quantum interference device and electrochemistry, assisted by density functional theory calculations. It was found that their diradical and tetraradical characters show a clear dependence on the fusion mode. Upon the introducing of more five-membered rings, the diradical characters greatly decrease. This difference can be explained by the pro-aromaticity/anti-aromaticity of the molecules as well as the intramolecular charge transfer. Our comprehensive studies provide a guideline for the design and synthesis of stable open-shell singlet polycyclic hydrocarbons with significant polyradical characters.

Towards Tetraradicaloid: The Effect of Fusion Mode on Radical Character and Chemical Reactivity

KAUST Repository

Hu, Pan; Lee, Sangsu; Herng, Tun Seng; Aratani, Naoki; Goncalves, Theo; Qi, Qingbiao; Shi, Xueliang; Yamada, Hiroko; Huang, Kuo-Wei; Ding, Jun; Kim, Dongho; Wu, Jishan

2015-01-01

Open-shell singlet diradicaloids display unique electronic, non-linear optical and magnetic activity and could become novel molecular materials for organic electronics, photonics and spintronics. However, design and synthesis of diradicaloids with a significant polyradical character is a challenging task for chemists. In this article, we report our efforts toward tetraradicaloid system. A series of potential tetraradicaloids by fusion of two p-quinodimethane (p-QDM) units with naphthalene or benzene rings in different modes were synthesized. Their model compounds containing one p-QDM moiety were also prepared and compared. Their ground-state structures, physical properties and chemical reactivity were systematically investigated by various exper-imental methods such as steady-state and transient absorption, two-photon absorption, X-ray crystallographic analysis, electron spin resonance, superconducting quantum interference device and electrochemistry, assisted by density functional theory calculations. It was found that their diradical and tetraradical characters show a clear dependence on the fusion mode. Upon the introducing of more five-membered rings, the diradical characters greatly decrease. This difference can be explained by the pro-aromaticity/anti-aromaticity of the molecules as well as the intramolecular charge transfer. Our comprehensive studies provide a guideline for the design and synthesis of stable open-shell singlet polycyclic hydrocarbons with significant polyradical characters.

Chinese Unknown Word Recognition for PCFG-LA Parsing

Directory of Open Access Journals (Sweden)

Qiuping Huang

2014-01-01

Full Text Available This paper investigates the recognition of unknown words in Chinese parsing. Two methods are proposed to handle this problem. One is the modification of a character-based model. We model the emission probability of an unknown word using the first and last characters in the word. It aims to reduce the POS tag ambiguities of unknown words to improve the parsing performance. In addition, a novel method, using graph-based semisupervised learning (SSL, is proposed to improve the syntax parsing of unknown words. Its goal is to discover additional lexical knowledge from a large amount of unlabeled data to help the syntax parsing. The method is mainly to propagate lexical emission probabilities to unknown words by building the similarity graphs over the words of labeled and unlabeled data. The derived distributions are incorporated into the parsing process. The proposed methods are effective in dealing with the unknown words to improve the parsing. Empirical results for Penn Chinese Treebank and TCT Treebank revealed its effectiveness.

Leading Character?s Antisocial Personality Disorder In James B Stewart?s Blind Eye

OpenAIRE

Lestari, Ayu

2016-01-01

110705043 The title of this thesis isLeading Character?s Antisocial Personality Disorder in James B Stewart?s Blind Eyethat is research about antisocial personality of leading character in the novel, namely Dr. Michael Swango. The purpose of this thesis is to find out characteristic of Swango that show he has antisocial personality disorder and to know the causes of his disorder. The writer refers to theory antisocial personality disorder that take in a research of APA (American Psychiatri...

Advanced optical correlation and digital methods for pattern matching—50th anniversary of Vander Lugt matched filter

Science.gov (United States)

Millán, María S.

2012-10-01

On the verge of the 50th anniversary of Vander Lugt’s formulation for pattern matching based on matched filtering and optical correlation, we acknowledge the very intense research activity developed in the field of correlation-based pattern recognition during this period of time. The paper reviews some domains that appeared as emerging fields in the last years of the 20th century and have been developed later on in the 21st century. Such is the case of three-dimensional (3D) object recognition, biometric pattern matching, optical security and hybrid optical-digital processors. 3D object recognition is a challenging case of multidimensional image recognition because of its implications in the recognition of real-world objects independent of their perspective. Biometric recognition is essentially pattern recognition for which the personal identification is based on the authentication of a specific physiological characteristic possessed by the subject (e.g. fingerprint, face, iris, retina, and multifactor combinations). Biometric recognition often appears combined with encryption-decryption processes to secure information. The optical implementations of correlation-based pattern recognition processes still rely on the 4f-correlator, the joint transform correlator, or some of their variants. But the many applications developed in the field have been pushing the systems for a continuous improvement of their architectures and algorithms, thus leading towards merged optical-digital solutions.

ANALYSIS OF THE INTERACTIONS BETWEEN IMMIGRANT/FOREIGN CHARACTERS AND NATIONAL/AUTOCHTHONOUS CHARACTERS IN SPANISH TELEVISION FICTION

Directory of Open Access Journals (Sweden)

María Marcos Ramos

2014-10-01

Full Text Available In this paper we present the results of an empirical research in which it were analysed the interactions between immigrants and national characters in a sample of Spanish television fictional programs broadcasted on prime time. This study is a content analysis of 282 interactions between immigrant/foreign and national characters. Thus, it was found that the largest number of relationships between the characters involved was produced in a working context. Moreover, there was a higher proportion of the use of aggressive humour from the national characters to the immigrant/foreigners than in the reverse way. It was also observed that the immigrant/foreigner characters hardly spoke about their feelings, nor were heard by the nationals when they did it, although there were a high number of interactions in which immigrant characters were expressing their opinions and these were attended by national characters. The analysis of the interactions between immigrant and national characters in television fiction is a very important research issue, because it has been proposed that the parasocial interactions are complementary of the interpersonal interactions taking place in daily life (Müller, 2009; Park, 2012.

THE NEED FOR CHARACTER EDUCATION

Directory of Open Access Journals (Sweden)

Aynur Pala

2011-07-01

Full Text Available Character education is a national movement creatingschools that foster ethical,responsible and caring young people by modelling and teaching good characterthrough emphasis on universal values that we all share. It is the intentional,proactive effort by schools, districts and states to instil in their students importantcore ethical values such as caring, honesty, fairness, responsibility and respect forself and others.Good character is not formed automatically; it is developed over time through asustained process of teaching, example, learning and practice. It is developedthrough character education. The intentional teaching of good character isparticularly important in today’s society since ouryouth face many opportunitiesand dangers unknown to earlier generations. They are bombarded with many morenegative influences through the media and other external sources prevalent intoday’s culture. Since children spend about 900 hours a year in school, it isessential that schools resume a proactive role in assisting families andcommunities by developing caring, respectful environments where students learncore, ethical values. When a comprehensive approachto character education isused, a positive moral culture is created in the school—a total school environmentthat supports the values taught in the classroom (Character Education Partnership,2010.The aim of this study is to provide guidelines forthe elements need for effectiveand comprehensive character education. And to emphasize the need of charactereducation to help students develop good character, which includes knowing,caring about and acting upon core ethical values such as respect, responsibility,honesty, fairness and compassion.

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

Holistic Processing of Chinese Characters

Directory of Open Access Journals (Sweden)

Alan Chun-Nang Wong

2011-05-01

Full Text Available Enhanced holistic processing (obligatory attention to all parts of an object has been associated with different types of perceptual expertise involving faces, cars, fingerprints, musical notes, English words, etc. Curiously Chinese characters are regarded as an exception, as indicated by the lack of holistic processing found for experts (Hsiao and Cottrell, 2009. The ceiling performance of experts, however, may have caused this null effect. We revisit this issue by adopting the often-used face-composite sequential-matching task to two-part Chinese characters. Participants matched the target halves (left or right of two characters while ignoring the irrelevant halves. Both Chinese readers (experts and non-Chinese readers (novices showed holistic processing. Follow-up experiments suggested different origins of the effects for the two groups. For experts, holistic processing was sensitive to the amount of experience with the characters, as it was larger for words than non-words (formed by swapping the two parts of a valid character. Novices, however, showed similar degree of holistic processing to words and non-words, suggesting that their effects were more related to their inefficient decomposition of a complex, character-like pattern into parts. Overall these findings suggest that holistic processing may be a marker of expertise with Chinese characters, contrary to previous claims.

Character order processing in Chinese reading.

Science.gov (United States)

Gu, Junjuan; Li, Xingshan; Liversedge, Simon P

2015-02-01

We explored how character order information is encoded in isolated word processing or Chinese sentence reading in 2 experiments using a masked priming paradigm and a gaze-contingent display-change paradigm. The results showed that response latencies in the lexical decision task and reading times on the target word region were longer in the unrelated condition (the prime or the preview was unrelated with the target word) than the transposed-character condition (the prime or the preview was a transposition of the 2 characters of the target word), which were respectively longer than in the identity condition (the prime or preview was identical to the target word). These results show that character order is encoded at an early stage of processing in Chinese reading, but character position encoding was not strict. We also found that character order encoding was similar for single-morpheme and multiple-morpheme words, suggesting that morphemic status does not affect character order encoding. The current results represent an early contribution to our understanding of character order encoding during Chinese reading.

Point spread function engineering for iris recognition system design.

Science.gov (United States)

Ashok, Amit; Neifeld, Mark A

2010-04-01

Undersampling in the detector array degrades the performance of iris-recognition imaging systems. We find that an undersampling of 8 x 8 reduces the iris-recognition performance by nearly a factor of 4 (on CASIA iris database), as measured by the false rejection ratio (FRR) metric. We employ optical point spread function (PSF) engineering via a Zernike phase mask in conjunction with multiple subpixel shifted image measurements (frames) to mitigate the effect of undersampling. A task-specific optimization framework is used to engineer the optical PSF and optimize the postprocessing parameters to minimize the FRR. The optimized Zernike phase enhanced lens (ZPEL) imager design with one frame yields an improvement of nearly 33% relative to a thin observation module by bounded optics (TOMBO) imager with one frame. With four frames the optimized ZPEL imager achieves a FRR equal to that of the conventional imager without undersampling. Further, the ZPEL imager design using 16 frames yields a FRR that is actually 15% lower than that obtained with the conventional imager without undersampling.

Targeted Query Expansions as a Method for Searching Mixed Quality Digitized Cultural Heritage Documents

NARCIS (Netherlands)

Keskustalo, H.; Kettunen, K.; Kumpulainen, S.; Ferro, N.; Silvello, G.; Järvelin, A.; Kekäläinen, J.; Arvola, P.; Saastamoinen, M.; Sormunen, E.; Järvelin, K.

2015-01-01

Digitization of cultural heritage is a huge ongoing effort in many countries. In digitized historical documents, words may occur in different surface forms due to three types of variation - morphological variation, historical variation, and errors in optical character recognition (OCR). Because

New Approach of Feature Extraction Method Based on the Raw Form and his Skeleton for Gujarati Handwritten Digits using Neural Networks Classifier

Directory of Open Access Journals (Sweden)

K. Moro

2014-12-01

Full Text Available This paper presents an optical character recognition (OCR system for Gujarati handwritten digits. One may find so much of work for latin writing, arabic, chines, etc. but Gujarati is a language for which hardly any work is traceable especially for handwritten characters. Here in this work we have proposed a method of feature extraction based on the raw form of the character and his skeleton and we have shown the advantage of using this method over other approaches mentioned in this article.

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.

Extraction and fusion of spectral parameters for face recognition

Science.gov (United States)

Boisier, B.; Billiot, B.; Abdessalem, Z.; Gouton, P.; Hardeberg, J. Y.

2011-03-01

Many methods have been developed in image processing for face recognition, especially in recent years with the increase of biometric technologies. However, most of these techniques are used on grayscale images acquired in the visible range of the electromagnetic spectrum. The aims of our study are to improve existing tools and to develop new methods for face recognition. The techniques used take advantage of the different spectral ranges, the visible, optical infrared and thermal infrared, by either combining them or analyzing them separately in order to extract the most appropriate information for face recognition. We also verify the consistency of several keypoints extraction techniques in the Near Infrared (NIR) and in the Visible Spectrum.

Quantitative analysis of eyes and other optical systems in linear optics.

Science.gov (United States)

Harris, William F; Evans, Tanya; van Gool, Radboud D

2017-05-01

To show that 14-dimensional spaces of augmented point P and angle Q characteristics, matrices obtained from the ray transference, are suitable for quantitative analysis although only the latter define an inner-product space and only on it can one define distances and angles. The paper examines the nature of the spaces and their relationships to other spaces including symmetric dioptric power space. The paper makes use of linear optics, a three-dimensional generalization of Gaussian optics. Symmetric 2 × 2 dioptric power matrices F define a three-dimensional inner-product space which provides a sound basis for quantitative analysis (calculation of changes, arithmetic means, etc.) of refractive errors and thin systems. For general systems the optical character is defined by the dimensionally-heterogeneous 4 × 4 symplectic matrix S, the transference, or if explicit allowance is made for heterocentricity, the 5 × 5 augmented symplectic matrix T. Ordinary quantitative analysis cannot be performed on them because matrices of neither of these types constitute vector spaces. Suitable transformations have been proposed but because the transforms are dimensionally heterogeneous the spaces are not naturally inner-product spaces. The paper obtains 14-dimensional spaces of augmented point P and angle Q characteristics. The 14-dimensional space defined by the augmented angle characteristics Q is dimensionally homogenous and an inner-product space. A 10-dimensional subspace of the space of augmented point characteristics P is also an inner-product space. The spaces are suitable for quantitative analysis of the optical character of eyes and many other systems. Distances and angles can be defined in the inner-product spaces. The optical systems may have multiple separated astigmatic and decentred refracting elements. © 2017 The Authors Ophthalmic & Physiological Optics © 2017 The College of Optometrists.

Optical actuation of micromechanical components

International Nuclear Information System (INIS)

Koehler, D.R.

1997-01-01

Electromagnetic momentum is a fundamental physical concept that has been demonstrated experimentally and incorporated theoretically in various areas of physics. In spite of the weak character of the electromagnetic momentum transfer process, the combination of latter-day, high-energy laser light sources and microminiature mechanical elements suggested the possibility of optical excitation of these structures. One outcome of the present theoretical analysis is the prediction of an optopiezic effect wherein electromagnetic momentum causes a mechanical stress on a dielectric layer. If this is a valid prediction, such an optically induced, expansional pressure effect could be utilized as an extensional optical-to-mechanical transduction means. copyright 1997 Optical Society of America

Where are the Search Engines for Handwritten Documents?

NARCIS (Netherlands)

van der Zant, Tijn; Schomaker, Lambert; Zinger, Svitlana; van Schie, Henny

Although the problems of optical character recognition for contemporary printed text have been resolved, for historical printed and handwritten connected cursive text (i.e. western style writing), they have not. This does not mean that scanning historical documents is not useful. This article

Where are the search engines for handwritten documents?

NARCIS (Netherlands)

Zant, T.; Schomaker, L.; Zinger, S.; Schie, H.

2009-01-01

Although the problems of optical character recognition for contemporary printed text have been resolved, for historical printed and handwritten connected cursive text (i.e. western style writing), they have not. This does not mean that scanning historical documents is not useful. This article

Character Development in Adolescents.

Science.gov (United States)

Kessler, Glenn R.; And Others

1986-01-01

Explored the effects of a program consisting of communication and counseling skills, assertiveness training and moral dilemmas on the character development of high school students. The results demonstrated that the character development of the students in the experimental treatment group was affected significantly over time by the program.…

Pattern recognition neural-net by spatial mapping of biology visual field

Science.gov (United States)

Lin, Xin; Mori, Masahiko

2000-05-01

The method of spatial mapping in biology vision field is applied to artificial neural networks for pattern recognition. By the coordinate transform that is called the complex-logarithm mapping and Fourier transform, the input images are transformed into scale- rotation- and shift- invariant patterns, and then fed into a multilayer neural network for learning and recognition. The results of computer simulation and an optical experimental system are described.

Deep--deeper--deepest? Encoding strategies and the recognition of human faces.

Science.gov (United States)

Sporer, S L

1991-03-01

Various encoding strategies that supposedly promote deeper processing of human faces (e.g., character judgments) have led to better recognition than more shallow processing tasks (judging the width of the nose). However, does deeper processing actually lead to an improvement in recognition, or, conversely, does shallow processing lead to a deterioration in performance when compared with naturally employed encoding strategies? Three experiments systematically compared a total of 8 different encoding strategies manipulating depth of processing, amount of elaboration, and self-generation of judgmental categories. All strategies that required a scanning of the whole face were basically equivalent but no better than natural strategy controls. The consistently worst groups were the ones that rated faces along preselected physical dimensions. This can be explained by subjects' lesser task involvement as revealed by manipulation checks.

Social character of materialism.

Science.gov (United States)

Chatterjee, A; Hunt, J M; Kernan, J B

2000-06-01

Scores for 170 undergraduates on Richins and Dawson's Materialism scale were correlated with scores on Kassarjian's Social Preference Scale, designed to measure individuals' character structure. A correlation of .26 between materialism and other-directed social character suggested that an externally oriented reference system guides materialists' perceptions, judgments, acquisitions, and possessions.

APLIKASI SPOKES-CHARACTERS DALAM KAITAN DENGAN MEREK PRODUK

Directory of Open Access Journals (Sweden)

Caroline Widjoyo

2004-01-01

Full Text Available Advertisement by using spokes-characters have potency to alter the choice of consumer brand with the compared to bigger impact which do not use the spokes-character. A lot of producer which hence spokes-character to increase assess to sell from a product. Spokes-Characters experience of the evolution from time to time keep abreast of the era%2C now emerge the new type of spokes-character and its application. Abstract in Bahasa Indonesia : Iklan dengan spokes-characters berpotensi mengubah pilihan merek konsumen dengan dampak lebih besar dibanding yang tidak menggunakan spokes-character. Banyak produsen yang memakai spokes-character untuk meningkatkan nilai jual dari sebuah produk. Spokes-characters mengalami evolusi dari masa ke masa mengikuti perkembangan jaman%2C sekarang muncul jenis baru spokes-character dan aplikasinya. spokes-characters%2C advertising%2C branding.

Character Play – The use of game characters in multi- player Role Playing Games across platforms

DEFF Research Database (Denmark)

Tychsen, Anders; Hitchens, M.; Brolund, T.

2008-01-01

histories of game characters. This article presents results from a comprehensive empirical study of the way complex game characters are utilized by players in multiplayer role-playing games across two different media platforms. The results indicate that adult players are capable of comprehending...... and utilizing game characters with well-defined personalities and backgrounds, as well as rules-based components. Furthermore, that the game format plays a significant role in the pattern of usage of the character elements. This pattern appears directly linked with variations in the way that the different game...

Marvel and DC Characters Inspired by Arachnids

Directory of Open Access Journals (Sweden)

Elidiomar Ribeiro Da-Silva

2014-12-01

Full Text Available This article compares arachnid-based Marvel and DC comics characters. The composition of a comic book character often has interesting ‘real-life’ influences. Given the strong connection between arachnids (especially spiders, scorpions and mites, all belonging to the zoological class 'Arachnida' and human beings it is not surprising that they have inspired many fictional characters. We recorded 84 Marvel Comics characters and 40 DC Comics characters, detailed in the dataset that accompanies the article (Da-Silva 2014. Most characters have been created recently, since the 1990s. Marvel has significantly more arachnid characters than DC. As for taxonomic classification, the characters were based mostly on spiders (zoological order 'Araneae'. Of the total characters, the majority are human beings, but an overwhelming number have at least some typical arachnid features. Villains (60.91% of total are significantly more numerous, considering the sum of the two publishers. Arachnids have bad reputation for being dangerous (Thorp and Woodson 1976; Ruppert and Barnes 1996. Since the public usually considers spiders, scorpions and mites “harmful” in general, we expected a larger contingent of villains. However, there was no statistical difference between the amount of villains and heroes in Marvel characters. It did not happen probably due to the success of one character: the Amazing Spider-Man.

Adjustment of gripping force by optical systems

Science.gov (United States)

Jalba, C. K.; Barz, C.

2018-01-01

With increasing automation, robotics also requires ever more intelligent solutions in the handling of various tasks. In this context, many grippers must also be re-designed. For this, they must always be adapted for different requirements. The equipment of the gripper systems with sensors should help to make the gripping process more intelligent. In order to achieve such objectives, optical systems can also be used. This work analyzes how the gripping force can be adjusted by means of an optical recognition. The result of this work is the creation of a connection between optical recognition, tolerances, gripping force and real-time control. In this way, algorithms can be created, with the aid of which robot grippers as well as other gripping systems become more intelligent.

Recognition of underground nuclear explosion and natural earthquake based on neural network

International Nuclear Information System (INIS)

Yang Hong; Jia Weimin

2000-01-01

Many features are extracted to improve the identified rate and reliability of underground nuclear explosion and natural earthquake. But how to synthesize these characters is the key of pattern recognition. Based on the improved Delta algorithm, features of underground nuclear explosion and natural earthquake are inputted into BP neural network, and friendship functions are constructed to identify the output values. The identified rate is up to 92.0%, which shows that: the way is feasible

Architecture of optical sensor for recognition of multiple toxic metal ions from water.

Science.gov (United States)

Shenashen, M A; El-Safty, S A; Elshehy, E A

2013-09-15

Here, we designed novel optical sensor based on the wormhole hexagonal mesoporous core/multi-shell silica nanoparticles that enabled the selective recognition and removal of these extremely toxic metals from drinking water. The surface-coating process of a mesoporous core/double-shell silica platforms by several consequence decorations using a cationic surfactant with double alkyl tails (CS-DAT) and then a synthesized dicarboxylate 1,5-diphenyl-3-thiocarbazone (III) signaling probe enabled us to create a unique hierarchical multi-shell sensor. In this design, the high loading capacity and wrapping of the CS-DAT and III organic moieties could be achieved, leading to the formation of silica core with multi-shells that formed from double-silica, CS-DAT, and III dressing layers. In this sensing system, notable changes in color and reflectance intensity of the multi-shelled sensor for Cu(2+), Co(2+), Cd(2+), and Hg(2+) ions, were observed at pH 2, 8, 9.5 and 11.5, respectively. The multi-shelled sensor is added to enable accessibility for continuous monitoring of several different toxic metal ions and efficient multi-ion sensing and removal capabilities with respect to reversibility, selectivity, and signal stability. Copyright © 2013 Elsevier B.V. All rights reserved.

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.

Handwritten Digits Recognition Using Neural Computing

Directory of Open Access Journals (Sweden)

Călin Enăchescu

2009-12-01

Full Text Available In this paper we present a method for the recognition of handwritten digits and a practical implementation of this method for real-time recognition. A theoretical framework for the neural networks used to classify the handwritten digits is also presented.The classification task is performed using a Convolutional Neural Network (CNN. CNN is a special type of multy-layer neural network, being trained with an optimized version of the back-propagation learning algorithm.CNN is designed to recognize visual patterns directly from pixel images with minimal preprocessing, being capable to recognize patterns with extreme variability (such as handwritten characters, and with robustness to distortions and simple geometric transformations.The main contributions of this paper are related to theoriginal methods for increasing the efficiency of the learning algorithm by preprocessing the images before the learning process and a method for increasing the precision and performance for real-time applications, by removing the non useful information from the background.By combining these strategies we have obtained an accuracy of 96.76%, using as training set the NIST (National Institute of Standards and Technology database.

Molecular recognition by gold, silver and copper nanoparticles

Science.gov (United States)

Tauran, Yannick; Brioude, Arnaud; Coleman, Anthony W; Rhimi, Moez; Kim, Beonjoom

2013-01-01

The intrinsic physical properties of the noble metal nanoparticles, which are highly sensitive to the nature of their local molecular environment, make such systems ideal for the detection of molecular recognition events. The current review describes the state of the art concerning molecular recognition of Noble metal nanoparticles. In the first part the preparation of such nanoparticles is discussed along with methods of capping and stabilization. A brief discussion of the three common methods of functionalization: Electrostatic adsorption; Chemisorption; Affinity-based coordination is given. In the second section a discussion of the optical and electrical properties of nanoparticles is given to aid the reader in understanding the use of such properties in molecular recognition. In the main section the various types of capping agents for molecular recognition; nucleic acid coatings, protein coatings and molecules from the family of supramolecular chemistry are described along with their numerous applications. Emphasis for the nucleic acids is on complementary oligonucleotide and aptamer recognition. For the proteins the recognition properties of antibodies form the core of the section. With respect to the supramolecular systems the cyclodextrins, calix[n]arenes, dendrimers, crown ethers and the cucurbitales are treated in depth. Finally a short section deals with the possible toxicity of the nanoparticles, a concern in public health. PMID:23977421

Character Education and Students Social Behavior

Directory of Open Access Journals (Sweden)

Syamsu A. Kamaruddin

2012-09-01

Full Text Available

In an educational environment, in the form of character education program has been done both formally and informally. It's intended as one of the supporting ideas for follow-up in the form of design activities. Character education should basically refers to the vision and mission of the institution concerned. It shows the orientation of the two things in the character of the students are: aspects of human character and individual learners hallmark institution. In this paper, these two aspects is the author trying to ideas by referring to some other writings. The end result, the authors expect the birth of a design patent as early referral to spearhead a character development program learners.

Automated extraction of radiation dose information from CT dose report images.

Science.gov (United States)

Li, Xinhua; Zhang, Da; Liu, Bob

2011-06-01

The purpose of this article is to describe the development of an automated tool for retrieving texts from CT dose report images. Optical character recognition was adopted to perform text recognitions of CT dose report images. The developed tool is able to automate the process of analyzing multiple CT examinations, including text recognition, parsing, error correction, and exporting data to spreadsheets. The results were precise for total dose-length product (DLP) and were about 95% accurate for CT dose index and DLP of scanned series.

All-Optical Network Subsystems Using Integrated SOA-Based Optical Gates and Flip-Flops for Label-Swapped Netorks

DEFF Research Database (Denmark)

Seoane, Jorge; Holm-Nielsen, Pablo Villanueva; Kehayas, E.

2006-01-01

In this letter, we demonstrate that all-optical network subsystems, offering intelligence in the optical layer, can be constructed by functional integration of integrated all-optical logic gates and flip-flops. In this context, we show 10-Gb/s all-optical 2-bit label address recognition......-level advantages of these all-optical subsystems combined with their realization with compact integrated devices, suggest that they are strong candidates for future packet/label switched optical networks....... by interconnecting two optical gates that perform xor operation on incoming optical labels. We also demonstrate 40-Gb/s all-optical wavelength-switching through an optically controlled wavelength converter, consisting of an integrated flip-flop prototype device driven by an integrated optical gate. The system...

Experimental demonstrations of all-optical networking functions for WDM optical networks

Science.gov (United States)

Gurkan, Deniz

The deployment of optical networks will enable high capacity links between users but will introduce the problems associated with transporting and managing more channels. Many network functions should be implemented in optical domain; main reasons are: to avoid electronic processing bottlenecks, to achieve data-format and data-rate independence, to provide reliable and cost efficient control and management information, to simultaneously process multiple wavelength channel operation for wavelength division multiplexed (WDM) optical networks. The following novel experimental demonstrations of network functions in the optical domain are presented: Variable-bit-rate recognition of the header information in a data packet. The technique is reconfigurable for different header sequences and uses optical correlators as look-up tables. The header is processed and a signal is sent to the switch for a series of incoming data packets at 155 Mb/s, 622 Mb/s, and 2.5 Gb/s in a reconfigurable network. Simultaneous optical time-slot-interchange and wavelength conversion of the bits in a 2.5-Gb/s data stream to achieve a reconfigurable time/wavelength switch. The technique uses difference-frequency-generation (DFG) for wavelength conversion and fiber Bragg gratings (FBG) as wavelength-dependent optical time buffers. The WDM header recognition module simultaneously recognizing two header bits on each of two 2.5-Gbit/s WDM packet streams. The module is tunable to enable reconfigurable look-up tables. Simultaneous and independent label swapping and wavelength conversion of two WDM channels for a multi-protocol label switching (MPLS) network. Demonstration of label swapping of distinct 8-bit-long labels for two WDM data channels is presented. Two-dimensional code conversion module for an optical code-division multiple-access (O-CDMA) local area network (LAN) system. Simultaneous wavelength conversion and time shifting is achieved to enable flexible code conversion and increase code re

Essays on Character & Opportunity

Science.gov (United States)

Center on Children and Families at Brookings, 2014

2014-01-01

These essays provide richer set of writings on the philosophical, empirical and practical issues raised by a focus on character, and in particular its relationship to questions of opportunity. Each one is an intellectual pemmican: sharp and to the point. Two scholars draw attention to the gendered nature of character formation (Segal and Lexmond);…

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…

The Effect of Realistic Appearance of Virtual Characters in Immersive Environments - Does the Character's Personality Play a Role?

Science.gov (United States)

Zibrek, Katja; Kokkinara, Elena; Mcdonnell, Rachel

2018-04-01

Virtual characters that appear almost photo-realistic have been shown to induce negative responses from viewers in traditional media, such as film and video games. This effect, described as the uncanny valley, is the reason why realism is often avoided when the aim is to create an appealing virtual character. In Virtual Reality, there have been few attempts to investigate this phenomenon and the implications of rendering virtual characters with high levels of realism on user enjoyment. In this paper, we conducted a large-scale experiment on over one thousand members of the public in order to gather information on how virtual characters are perceived in interactive virtual reality games. We were particularly interested in whether different render styles (realistic, cartoon, etc.) would directly influence appeal, or if a character's personality was the most important indicator of appeal. We used a number of perceptual metrics such as subjective ratings, proximity, and attribution bias in order to test our hypothesis. Our main result shows that affinity towards virtual characters is a complex interaction between the character's appearance and personality, and that realism is in fact a positive choice for virtual characters in virtual reality.

Kurzweil Reading Machine: A Partial Evaluation of Its Optical Character Recognition Error Rate.

Science.gov (United States)

Goodrich, Gregory L.; And Others

1979-01-01

A study designed to assess the ability of the Kurzweil reading machine (a speech reading device for the visually handicapped) to read three different type styles produced by five different means indicated that the machines tested had different error rates depending upon the means of producing the copy and upon the type style used. (Author/CL)

Promoting Character Development through Coach Education

Science.gov (United States)

Power, F. Clark; Seroczynski, A. D.

2015-01-01

Can youth sports build character? Research suggests that the answer to this question leads to 2 further questions: (1) can youth sport coaches be effectively prepared to become character educators, and (2) can character education take place in today's competitive youth sport environment? (Bredemeier & Shields, 2006; Power, 2015; Power &…

Identifying hidden rate changes in the evolution of a binary morphological character: the evolution of plant habit in campanulid angiosperms.

Science.gov (United States)

Beaulieu, Jeremy M; O'Meara, Brian C; Donoghue, Michael J

2013-09-01

The growth of phylogenetic trees in scope and in size is promising from the standpoint of understanding a wide variety of evolutionary patterns and processes. With trees comprised of larger, older, and globally distributed clades, it is likely that the lability of a binary character will differ significantly among lineages, which could lead to errors in estimating transition rates and the associated inference of ancestral states. Here we develop and implement a new method for identifying different rates of evolution in a binary character along different branches of a phylogeny. We illustrate this approach by exploring the evolution of growth habit in Campanulidae, a flowering plant clade containing some 35,000 species. The distribution of woody versus herbaceous species calls into question the use of traditional models of binary character evolution. The recognition and accommodation of changes in the rate of growth form evolution in different lineages demonstrates, for the first time, a robust picture of growth form evolution across a very large, very old, and very widespread flowering plant clade.

A Study of Character among Collegiate Athletes

Science.gov (United States)

Heupel, Jill D.

2017-01-01

The idea that sport builds character has been around for a long time. However, sports may not build the type of character once thought. Character of athletes was defined based on differing views held by sport scholars, coaches, athletes, and sport enthusiast. Sport scholars tend to view character of athletes from a moral perspective. Coaches,…

Design and Implementation of Behavior Recognition System Based on Convolutional Neural Network

Directory of Open Access Journals (Sweden)

Yu Bo

2017-01-01

Full Text Available We build a set of human behavior recognition system based on the convolution neural network constructed for the specific human behavior in public places. Firstly, video of human behavior data set will be segmented into images, then we process the images by the method of background subtraction to extract moving foreground characters of body. Secondly, the training data sets are trained into the designed convolution neural network, and the depth learning network is constructed by stochastic gradient descent. Finally, the various behaviors of samples are classified and identified with the obtained network model, and the recognition results are compared with the current mainstream methods. The result show that the convolution neural network can study human behavior model automatically and identify human’s behaviors without any manually annotated trainings.

Body Language Advanced 3D Character Rigging

CERN Document Server

Allen, Eric; Fong, Jared; Sidwell, Adam G

2011-01-01

Whether you're a professional Character TD or just like to create 3D characters, this detailed guide reveals the techniques you need to create sophisticated 3D character rigs that range from basic to breathtaking. Packed with step-by-step instructions and full-color illustrations, Body Language walks you through rigging techniques for all the body parts to help you create realistic and believable movements in every character you design. You'll learn advanced rigging concepts that involve MEL scripting and advanced deformation techniques and even how to set up a character pipeline.

Application of Freeman Chain Codes: An Alternative Recognition Technique for Malaysian Car Plates

OpenAIRE

Jusoh, Nor Amizam; Zain, Jasni Mohamad

2011-01-01

Various applications of car plate recognition systems have been developed using various kinds of methods and techniques by researchers all over the world. The applications developed were only suitable for specific country due to its standard specification endorsed by the transport department of particular countries. The Road Transport Department of Malaysia also has endorsed a specification for car plates that includes the font and size of characters that must be followed by car owners. Howev...

Data Input for Libraries: State-of-the-Art Report.

Science.gov (United States)

Buckland, Lawrence F.

This brief overview of new manuscript preparation methods which allow authors and editors to set their own type discusses the advantages and disadvantages of optical character recognition (OCR), microcomputers and personal computers, minicomputers, and word processors for editing and database entry. Potential library applications are also…

On Hemingway’s Literary Characters

Directory of Open Access Journals (Sweden)

Maria-Miruna Ciocoi-Pop

2013-01-01

Full Text Available The present paper is a brief outline of Hemingway’s characters and the way in which they correspond to the author himself. It is known for a fact that Hemingway evinced a tendency to imitate his characters when they were coming to grips with diverse situations. Thus I have tried to briefly pinpoint the fading boundaries between reality and imagination in his work. By doing so, I have focused on both male and female characters, underlining the major dissimilarities between these two categories, as well as their main features.

Moral character effects in endorser perception

Directory of Open Access Journals (Sweden)

Chang Joseph W.

2017-06-01

Full Text Available This research consists of two experimental studies investigating the influence of moral character on endorser perception, and the influence of perceiver characteristics on tarnished endorser perception and brand evaluations. Perceiver characteristics are discussed from the perspectives of dispositional tendency, innate moral intuitions and self-location. The first study compared the influences of moral character and warmth on endorser perception. The second study examined the impact of perceiver characteristics on tarnished endorsers and brand evaluations. The findings reveal that moral character is more influential than warmth on endorser evaluations. Tarnished endorsers with immoral character exert more negative influence than tarnished endorsers with coldness character on brand evaluations. Innate moral intuitions and self-location moderate brand evaluations. High-morality consumers and heart-locators are more vulnerable than low-morality and brain-locators to the brands endorsed by tarnished endorsers, respectively.

The Effect of Attractiveness on Recognition Memory when Women Look at Female Faces

Directory of Open Access Journals (Sweden)

Kana Kuraguchi

2011-05-01

Full Text Available In previous studies, the relationship between facial attractiveness and memory has been inconsistent. We investigated the effect of facial attractiveness on recognition memory in terms of gender and judgment contents. Both female and male facial images were judged for their attractiveness and personal character, and incidental memory was tested later. Recognition performance was shown as d' and analyzed with 2 (participant's gender x 2 (condition of attractiveness ANOVA. The interaction was significant for female faces but not for male faces. It is, therefore, suggested that the difference of gender affects the recognition memory concerning facial attractiveness. In particular, attractiveness of female faces had different effects for female participants when compared to other combinations. As a control, the interaction for female faces was not significant when the task was to judge the physical features such as the size of eyes and the angle of mouth. In sum, unattractive faces were better recognized than attractive faces in general except for the case when women judged attractiveness of female faces. These results suggest that there may be an effect of attention to attractiveness on recognition memory that is particularly strong when women look at female faces.

Video Game Characters. Theory and Analysis

Directory of Open Access Journals (Sweden)

Felix Schröter

2014-06-01

Full Text Available This essay develops a method for the analysis of video game characters based on a theoretical understanding of their medium-specific representation and the mental processes involved in their intersubjective construction by video game players. We propose to distinguish, first, between narration, simulation, and communication as three modes of representation particularly salient for contemporary video games and the characters they represent, second, between narrative, ludic, and social experience as three ways in which players perceive video game characters and their representations, and, third, between three dimensions of video game characters as ‘intersubjective constructs’, which usually are to be analyzed not only as fictional beings with certain diegetic properties but also as game pieces with certain ludic properties and, in those cases in which they function as avatars in the social space of a multiplayer game, as representations of other players. Having established these basic distinctions, we proceed to analyze their realization and interrelation by reference to the character of Martin Walker from the third-person shooter Spec Ops: The Line (Yager Development 2012, the highly customizable player-controlled characters from the role-playing game The Elder Scrolls V: Skyrim (Bethesda 2011, and the complex multidimensional characters in the massively multiplayer online role-playing game Star Wars: The Old Republic (BioWare 2011-2014.

Thomas Young's contributions to geometrical optics.

Science.gov (United States)

Atchison, David A; Charman, W Neil

2011-07-01

In addition to his work on physical optics, Thomas Young (1773-1829) made several contributions to geometrical optics, most of which received little recognition in his time or since. We describe and assess some of these contributions: Young's construction (the basis for much of his geometric work), paraxial refraction equations, oblique astigmatism and field curvature, and gradient-index optics. © 2011 The Authors. Clinical and Experimental Optometry © 2011 Optometrists Association Australia.

Phylogeny of the Acanthocephala based on morphological characters.

Science.gov (United States)

Monks, S

2001-02-01

Only four previous studies of relationships among acanthocephalans have included cladistic analyses, and knowledge of the phylogeny of the group has not kept pace with that of other taxa. The purpose of this study is to provide a more comprehensive analysis of the phylogenetic relationships among members of the phylum Acanthocephala using morphological characters. The most appropriate outgroups are those that share a common early cell-cleavage pattern (polar placement of centrioles), such as the Rotifera, rather than the Priapulida (meridional placement of centrioles) to provide character polarity based on common ancestry rather than a general similarity likely due to convergence of body shapes. The phylogeny of 22 species of the Acanthocephala was evaluated based on 138 binary and multistate characters derived from comparative morphological and ontogenetic studies. Three assumptions of cement gland structure were tested: (i) the plesiomorphic type of cement glands in the Rotifera, as the sister group, is undetermined; (ii) non-syncytial cement glands are plesiomorphic; and (iii) syncytial cement glands are plesiomorphic. The results were used to test an early move of Tegorhynchus pectinarius to Koronacantha and to evaluate the relationship between Tegorhynchus and Illiosentis. Analysis of the data-set for each of these assumptions of cement gland structure produced the same single most parsimonious tree topology. Using Assumptions i and ii for the cement glands, the trees were the same length (length = 404 steps, CI = 0.545, CIX = 0.517, HI = 0.455, HIX = 0.483, RI = 0.670, RC = 0.365). Using Assumption iii, the tree was three steps longer (length = 408 steps, CI = 0.539, CIX = 0.512, HI = 0.461, HIX = 0.488, RI = 0.665, RC = 0.359). The tree indicates that the Palaeacanthocephala and Eoacanthocephala both are monophyletic and are sister taxa. The members of the Archiacanthocephala are basal to the other two clades, but do not themselves form a clade. The results

Modeling the Semiotic Structure of Player-Characters

DEFF Research Database (Denmark)

Vella, Daniel

2014-01-01

When game studies has tackled the player-character, it has tended to do so by means of an opposition to the notion of the avatar, with the result that the ontological and semiotic nature of the character in itself has not been given due attention. This paper draws on understandings of character...... from the fields of narratology and literary theory to highlight the double-layered ontology of character as both a possible individual and as a semiotic construction. Uri Margolin’s narratological model of character signification is used as the basis for developing a semiotic-structural model...

Building innovative and creative character through mathematics

Science.gov (United States)

Suyitno, Hardi; Suyitno, Amin

2018-03-01

21st century is predicted as the century with rapid development in all aspects of life. People require creative and innovative character to exist. Specifically, mathematics has been given to students from the kindergarten until the middle school. Thus, building character through mathematics should begin since the early age. The problem is how to build creative and innovative character through mathematics education? The goal expected from this question is to build innovative and creative characters to face the challenges of the 21st century. This article discusses the values of mathematics, the values in mathematics education, innovative and creative character, and the integration of these values in teaching mathematics that support the innovative and creative character building, and applying the values in structurely programmed, measurable, and applicable learning activities.

Virtual Character Personality Influences Participant Attitudes and Behavior - An Interview with a Virtual Human Character about Her Social Anxiety

Directory of Open Access Journals (Sweden)

Xueni ePan

2015-02-01

Full Text Available We introduce a novel technique for the study of human-virtual character interaction in immersive virtual reality. The human participants verbally administered a standard questionnaire about social anxiety to a virtual female character, that responded to each question through speech and body movements. The purpose was to study the extent to which participants responded differently to characters that exhibited different personalities, even though the verbal content of their answers was always the same. A separate online study provided evidence that our intention to create two different personality types had been successful. In the main between-groups experiment that utilized a Cave system there were 24 male participants, where 12 interacted with a female virtual character portrayed to exhibit shyness and the remaining 12 with an identical but more confident virtual character. Our results indicate that although the content of the verbal responses of both virtual characters was the same, participants showed different subjective and behavioral responses to the two different personalities. In particular participants evaluated the shy character more positively, for example, expressing willingness to spend more time with her. Participants evaluated the confident character more negatively and waited for a significantly longer time to call her back after she had left the scene in order to answer a telephone call. The method whereby participants interviewed the virtual character allowed naturalistic conversation while avoiding the necessity of speech processing and generation, and natural language understanding. It is therefore a useful method for the study of the impact of virtual character personality on participant responses.

Character Education in Print: Content Analysis of Character Education in Introduction to Education Textbooks

Science.gov (United States)

Protz, Babette Marisa

2013-01-01

Albert Einstein is credited with saying that the most important component of education is the development of students' character. While debate exists as to the delivery of character education in the public schools, it must be recognized that not all students have a support system outside of the schoolhouse. Consequently, when character…

Rotation, scale, and translation invariant pattern recognition using feature extraction

Science.gov (United States)

Prevost, Donald; Doucet, Michel; Bergeron, Alain; Veilleux, Luc; Chevrette, Paul C.; Gingras, Denis J.

1997-03-01

A rotation, scale and translation invariant pattern recognition technique is proposed.It is based on Fourier- Mellin Descriptors (FMD). Each FMD is taken as an independent feature of the object, and a set of those features forms a signature. FMDs are naturally rotation invariant. Translation invariance is achieved through pre- processing. A proper normalization of the FMDs gives the scale invariance property. This approach offers the double advantage of providing invariant signatures of the objects, and a dramatic reduction of the amount of data to process. The compressed invariant feature signature is next presented to a multi-layered perceptron neural network. This final step provides some robustness to the classification of the signatures, enabling good recognition behavior under anamorphically scaled distortion. We also present an original feature extraction technique, adapted to optical calculation of the FMDs. A prototype optical set-up was built, and experimental results are presented.

New technique for real-time distortion-invariant multiobject recognition and classification

Science.gov (United States)

Hong, Rutong; Li, Xiaoshun; Hong, En; Wang, Zuyi; Wei, Hongan

2001-04-01

A real-time hybrid distortion-invariant OPR system was established to make 3D multiobject distortion-invariant automatic pattern recognition. Wavelet transform technique was used to make digital preprocessing of the input scene, to depress the noisy background and enhance the recognized object. A three-layer backpropagation artificial neural network was used in correlation signal post-processing to perform multiobject distortion-invariant recognition and classification. The C-80 and NOA real-time processing ability and the multithread programming technology were used to perform high speed parallel multitask processing and speed up the post processing rate to ROIs. The reference filter library was constructed for the distortion version of 3D object model images based on the distortion parameter tolerance measuring as rotation, azimuth and scale. The real-time optical correlation recognition testing of this OPR system demonstrates that using the preprocessing, post- processing, the nonlinear algorithm os optimum filtering, RFL construction technique and the multithread programming technology, a high possibility of recognition and recognition rate ere obtained for the real-time multiobject distortion-invariant OPR system. The recognition reliability and rate was improved greatly. These techniques are very useful to automatic target recognition.

Landscape Character of Pongkor Mining Ecotourism Area

Science.gov (United States)

Kusumoarto, A.; Gunawan, A.; Machfud; Hikmat, A.

2017-10-01

Pongkor Mining Ecotourism Area has a diverse landscape character as a potential landscape resources for the development of ecotourism destination. This area is part of the Mount of Botol Resort, Halimun Salak National Park (HSNP). This area also has a fairly high biodiversity. This study aims to identify and analysis the category of landscape character in the Pongkor Mining Ecotourism Area for the development of ecotourism destination. This study used a descriptive approach through field surveys and interviews, was carried out through two steps : 1) identify the landscape character, and 2) analysis of the landscape character. The results showed that in areas set aside for ecotourism destination in Pongkor Mining, landscape character category scattered forests, tailing ponds, river, plain, and the built environment. The Category of landscape character most dominant scattered in the area is forest, here is the river, plain, tailing ponds, the built environment, and plain. The landscape character in a natural environment most preferred for ecotourism activities. The landscape character that spread in the natural environment and the built environment is a potential that must be protected and modified such as elimination of incongruous element, accentuation of natural form, alteration of the natural form, intensification and enhanced visual quality intensively to be developed as a ecotourism destination area.

READING LITERATURE, TAKING PHILOSOPHICAL IDEAS, AND OBTAINING CHARACTERS

Directory of Open Access Journals (Sweden)

Siti Maisaroh

2017-05-01

Full Text Available This study aims to describe the philosophical ideas and characters containing in trilogy of 'RaraMendut's' novel by YB Mangunwijaya. The method used is the knowledge archeology of Michel Foucault. The research proves that the philosophical ideas as follows: 1 wife's faithfulness contains characters of wife’s strong determination and true faithfulness sense; 2 The women seizing fate's  contains the character of high struggle spirit;3 women as a glory’s symbol contains character of self-actualization ability; 4 women and a country's defense contains a character of clever to take on the role / responsive; 5 women and their benefits contains the character as a source of love and life spirit; 6 women as good mothers contains the character of conciliatory, reassuring, joyful, sincere, and full of love; 7 the anxiety to old age contains the character of religious and strong self-awareness; 8 the glory contains the character of the glory of battle with themselves; 9 the child's nature contains the character of belief in the skill/ creativity of children and believe to God the Evolver; And 10 the essence of wisdom and usefulness of life contain  the characters of uniting the scattered things, receiving and embracing sincerely things bad/ broken/ waste, understanding and forgiving, voice sincerity and excitement, not easy to complain.

Emotion Recognition in Frontotemporal Dementia and Alzheimer's Disease: A New Film-Based Assessment

Science.gov (United States)

Goodkind, Madeleine S.; Sturm, Virginia E.; Ascher, Elizabeth A.; Shdo, Suzanne M.; Miller, Bruce L.; Rankin, Katherine P.; Levenson, Robert W.

2015-01-01

Deficits in recognizing others' emotions are reported in many psychiatric and neurological disorders, including autism, schizophrenia, behavioral variant frontotemporal dementia (bvFTD) and Alzheimer's disease (AD). Most previous emotion recognition studies have required participants to identify emotional expressions in photographs. This type of assessment differs from real-world emotion recognition in important ways: Images are static rather than dynamic, include only 1 modality of emotional information (i.e., visual information), and are presented absent a social context. Additionally, existing emotion recognition batteries typically include multiple negative emotions, but only 1 positive emotion (i.e., happiness) and no self-conscious emotions (e.g., embarrassment). We present initial results using a new task for assessing emotion recognition that was developed to address these limitations. In this task, respondents view a series of short film clips and are asked to identify the main characters' emotions. The task assesses multiple negative, positive, and self-conscious emotions based on information that is multimodal, dynamic, and socially embedded. We evaluate this approach in a sample of patients with bvFTD, AD, and normal controls. Results indicate that patients with bvFTD have emotion recognition deficits in all 3 categories of emotion compared to the other groups. These deficits were especially pronounced for negative and self-conscious emotions. Emotion recognition in this sample of patients with AD was indistinguishable from controls. These findings underscore the utility of this approach to assessing emotion recognition and suggest that previous findings that recognition of positive emotion was preserved in dementia patients may have resulted from the limited sampling of positive emotion in traditional tests. PMID:26010574

Emotion recognition in frontotemporal dementia and Alzheimer's disease: A new film-based assessment.

Science.gov (United States)

Goodkind, Madeleine S; Sturm, Virginia E; Ascher, Elizabeth A; Shdo, Suzanne M; Miller, Bruce L; Rankin, Katherine P; Levenson, Robert W

2015-08-01

Deficits in recognizing others' emotions are reported in many psychiatric and neurological disorders, including autism, schizophrenia, behavioral variant frontotemporal dementia (bvFTD) and Alzheimer's disease (AD). Most previous emotion recognition studies have required participants to identify emotional expressions in photographs. This type of assessment differs from real-world emotion recognition in important ways: Images are static rather than dynamic, include only 1 modality of emotional information (i.e., visual information), and are presented absent a social context. Additionally, existing emotion recognition batteries typically include multiple negative emotions, but only 1 positive emotion (i.e., happiness) and no self-conscious emotions (e.g., embarrassment). We present initial results using a new task for assessing emotion recognition that was developed to address these limitations. In this task, respondents view a series of short film clips and are asked to identify the main characters' emotions. The task assesses multiple negative, positive, and self-conscious emotions based on information that is multimodal, dynamic, and socially embedded. We evaluate this approach in a sample of patients with bvFTD, AD, and normal controls. Results indicate that patients with bvFTD have emotion recognition deficits in all 3 categories of emotion compared to the other groups. These deficits were especially pronounced for negative and self-conscious emotions. Emotion recognition in this sample of patients with AD was indistinguishable from controls. These findings underscore the utility of this approach to assessing emotion recognition and suggest that previous findings that recognition of positive emotion was preserved in dementia patients may have resulted from the limited sampling of positive emotion in traditional tests. (c) 2015 APA, all rights reserved).

Kansas State University Libraries' OCR Labeling Project.

Science.gov (United States)

Thierer, Joyce; Bower, Merry

This publication describes the planning and implementation of an optical character recognition (OCR) labeling project, the first stage of Kansas State University (KSU) Libraries' program of conversion from a manual to an automated circulation system. It is noted that a telephone survey of libraries with automated circulation systems and…

Effects of OCR Errors on Ranking and Feedback Using the Vector Space Model.

Science.gov (United States)

Taghva, Kazem; And Others

1996-01-01

Reports on the performance of the vector space model in the presence of OCR (optical character recognition) errors in information retrieval. Highlights include precision and recall, a full-text test collection, smart vector representation, impact of weighting parameters, ranking variability, and the effect of relevance feedback. (Author/LRW)

Sadhana | Indian Academy of Sciences

Indian Academy of Sciences (India)

A survey on optical character recognition for Bangla and Devanagari scripts · Soumen Bag ... 2016 pp 643-652. Experimental and numerical analysis for optimal design parameters of a falling film evaporator ... 2017 pp 517-531. A study of energy transfer during water entry of solids using incompressible SPH simulations.

Comparison of brain mechanisms underlying the processing of Chinese characters and pseudo-characters: an event-related potential study.

Science.gov (United States)

Wang, Ting; Li, Hong; Zhang, Qinglin; Tu, Shen; Yu, Caiyun; Qiu, Jiang

2010-04-01

Most Chinese characters are composed of a semantic radical on the left and a phonetic radical on the right. The semantic radical provides the semantic information; the phonetic radical provides information concerning the pronunciation of the whole character. The pseudo-characters in the study consisted of different sub-lexical parts of real Chinese characters and consequently they also had the semantic radical and the phonetic radical. But they were not readable and had no actual meaning. In order to investigate the spatiotemporal cortical activation patterns underlying the orthographic, phonological and semantic processing of Chinese characters, we used event-related brain potentials (ERPs) to explore the processing of Chinese characters and pseudo-characters when 14 healthy Chinese college students viewed the characters passively. Results showed that both Chinese characters and pseudo-characters elicited an evident negative potential peaking around 120 ms (N120), which appeared to reflect initial orthographic distinction and evaluation. Then, Chinese pseudo-characters elicited a more positive ERP deflection (P220) than did Chinese characters 200-250 ms after onset of the stimuli. It was similar to the recognition potential (RP) and might reflect the integration processes of phonological and semantic processing on the basis of early orthographic information. Dipole source analysis of the difference wave (pseudo-characters minus characters) indicated that a generator localized in the left temporal-occipital junction contributed to this effect, which was possibly related to phonological and perceptual-semantic information integration. Between 350-450 ms, a greater negativity (N360) in pseudo-characters as compared to characters was found over midline fronto-central scalp regions. Dipole analysis localized the generator of N360 in the right parahippocampal cortex. Therefore, the N360 might be an N400 component and reflect the higher-level semantic activation on the

A Classification Scheme for Literary Characters

Directory of Open Access Journals (Sweden)

Matthew Berry

2017-10-01

Full Text Available There is no established classification scheme for literary characters in narrative theory short of generic categories like protagonist vs. antagonist or round vs. flat. This is so despite the ubiquity of stock characters that recur across media, cultures, and historical time periods. We present here a proposal of a systematic psychological scheme for classifying characters from the literary and dramatic fields based on a modification of the Thomas-Kilmann (TK Conflict Mode Instrument used in applied studies of personality. The TK scheme classifies personality along the two orthogonal dimensions of assertiveness and cooperativeness. To examine the validity of a modified version of this scheme, we had 142 participants provide personality ratings for 40 characters using two of the Big Five personality traits as well as assertiveness and cooperativeness from the TK scheme. The results showed that assertiveness and cooperativeness were orthogonal dimensions, thereby supporting the validity of using a modified version of TK’s two-dimensional scheme for classifying characters.

[A wavelet neural network algorithm of EEG signals data compression and spikes recognition].

Science.gov (United States)

Zhang, Y; Liu, A; Yu, K

1999-06-01

A novel method of EEG signals compression representation and epileptiform spikes recognition based on wavelet neural network and its algorithm is presented. The wavelet network not only can compress data effectively but also can recover original signal. In addition, the characters of the spikes and the spike-slow rhythm are auto-detected from the time-frequency isoline of EEG signal. This method is well worth using in the field of the electrophysiological signal processing and time-frequency analyzing.

Character, attitude and disposition

OpenAIRE

Webber, Jonathan

2015-01-01

Recent debate over the empirical psychological presuppositions of virtue ethics has focused on reactive behavioural dispositions. But there are many character traits that cannot be understood properly in this way. Such traits are well described by attitude psychology. Moreover, the findings of attitude psychology support virtue ethics in three ways. First, they confirm the role of habituation in the development of character. Further, they show virtue ethics to be compatible with the situation...

Extending the imaging volume for biometric iris recognition.

Science.gov (United States)

Narayanswamy, Ramkumar; Johnson, Gregory E; Silveira, Paulo E X; Wach, Hans B

2005-02-10

The use of the human iris as a biometric has recently attracted significant interest in the area of security applications. The need to capture an iris without active user cooperation places demands on the optical system. Unlike a traditional optical design, in which a large imaging volume is traded off for diminished imaging resolution and capacity for collecting light, Wavefront Coded imaging is a computational imaging technology capable of expanding the imaging volume while maintaining an accurate and robust iris identification capability. We apply Wavefront Coded imaging to extend the imaging volume of the iris recognition application.

PC-based car license plate reader

Science.gov (United States)

Hwang, Chung-Mu; Shu, Shyh-Yeong; Chen, Wen-Yu; Chen, Yie-Wern; Wen, Kuang-Pu

1992-11-01

A car license plate reader (CLPR) using fuzzy inference and neural network algorithm has been developed in Industrial Technology Research Institute (ITRI) and installed in highway toll stations to identify stolen cars. It takes an average of 0.7 seconds to recognize a car license plate by using a PC with 80486-50 CPU. The recognition rate of the system is about 97%. The techniques of CLPR include vehicle sensing, image grab control, optic pre- processing, lighting, and optic character recognition (OCR). The CLPR can be used in vehicle flow statistics, the checking of stolen vehicles, automatic charging systems in parking lots or garage management, and so on.

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

2017-01-01

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…

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.

Detection, recognition, identification, and tracking of military vehicles using biomimetic intelligence

Science.gov (United States)

Pace, Paul W.; Sutherland, John

2001-10-01

This project is aimed at analyzing EO/IR images to provide automatic target detection/recognition/identification (ATR/D/I) of militarily relevant land targets. An increase in performance was accomplished using a biomimetic intelligence system functioning on low-cost, commercially available processing chips. Biomimetic intelligence has demonstrated advanced capabilities in the areas of hand- printed character recognition, real-time detection/identification of multiple faces in full 3D perspectives in cluttered environments, advanced capabilities in classification of ground-based military vehicles from SAR, and real-time ATR/D/I of ground-based military vehicles from EO/IR/HRR data in cluttered environments. The investigation applied these tools to real data sets and examined the parameters such as the minimum resolution for target recognition, the effect of target size, rotation, line-of-sight changes, contrast, partial obscuring, background clutter etc. The results demonstrated a real-time ATR/D/I capability against a subset of militarily relevant land targets operating in a realistic scenario. Typical results on the initial EO/IR data indicate probabilities of correct classification of resolved targets to be greater than 95 percent.

New methods of subcooled water recognition in dew point hygrometers

Science.gov (United States)

Weremczuk, Jerzy; Jachowicz, Ryszard

2001-08-01

Two new methods of sub-cooled water recognition in dew point hygrometers are presented in this paper. The first one- impedance method use a new semiconductor mirror in which the dew point detector, the thermometer and the heaters were integrated all together. The second one an optical method based on a multi-section optical detector is discussed in the report. Experimental results of both methods are shown. New types of dew pont hydrometers of ability to recognized sub-cooled water were proposed.

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.

Leadership, character and its development: A qualitative exploration

Directory of Open Access Journals (Sweden)

Roslyn de Braine

2007-11-01

Full Text Available The purpose of this study was to explore (1 what organisational leaders consider to be character elements of leaders within the workplace, (2 what influences leaders’ character development, and (3 how an organisation can continue the process of character development. The literature review and findings revealed that leadership, integrity, industriousness, empathy, loyalty, optimism, fairness and compassion are the most sought after character elements within leaders in the workplace. Leadership and integrity were found to be the most supported character elements. The findings also indicate that work environmental factors, a person’s own efforts, and the daily experiences of work life contribute towards character development.

Dual Temporal Scale Convolutional Neural Network for Micro-Expression Recognition

Directory of Open Access Journals (Sweden)

Min Peng

2017-10-01

Full Text Available Facial micro-expression is a brief involuntary facial movement and can reveal the genuine emotion that people try to conceal. Traditional methods of spontaneous micro-expression recognition rely excessively on sophisticated hand-crafted feature design and the recognition rate is not high enough for its practical application. In this paper, we proposed a Dual Temporal Scale Convolutional Neural Network (DTSCNN for spontaneous micro-expressions recognition. The DTSCNN is a two-stream network. Different of stream of DTSCNN is used to adapt to different frame rate of micro-expression video clips. Each stream of DSTCNN consists of independent shallow network for avoiding the overfitting problem. Meanwhile, we fed the networks with optical-flow sequences to ensure that the shallow networks can further acquire higher-level features. Experimental results on spontaneous micro-expression databases (CASME I/II showed that our method can achieve a recognition rate almost 10% higher than what some state-of-the-art method can achieve.

Dual Temporal Scale Convolutional Neural Network for Micro-Expression Recognition.

Science.gov (United States)

Peng, Min; Wang, Chongyang; Chen, Tong; Liu, Guangyuan; Fu, Xiaolan

2017-01-01

Facial micro-expression is a brief involuntary facial movement and can reveal the genuine emotion that people try to conceal. Traditional methods of spontaneous micro-expression recognition rely excessively on sophisticated hand-crafted feature design and the recognition rate is not high enough for its practical application. In this paper, we proposed a Dual Temporal Scale Convolutional Neural Network (DTSCNN) for spontaneous micro-expressions recognition. The DTSCNN is a two-stream network. Different of stream of DTSCNN is used to adapt to different frame rate of micro-expression video clips. Each stream of DSTCNN consists of independent shallow network for avoiding the overfitting problem. Meanwhile, we fed the networks with optical-flow sequences to ensure that the shallow networks can further acquire higher-level features. Experimental results on spontaneous micro-expression databases (CASME I/II) showed that our method can achieve a recognition rate almost 10% higher than what some state-of-the-art method can achieve.

Dual Temporal Scale Convolutional Neural Network for Micro-Expression Recognition

Science.gov (United States)

Peng, Min; Wang, Chongyang; Chen, Tong; Liu, Guangyuan; Fu, Xiaolan

2017-01-01

Facial micro-expression is a brief involuntary facial movement and can reveal the genuine emotion that people try to conceal. Traditional methods of spontaneous micro-expression recognition rely excessively on sophisticated hand-crafted feature design and the recognition rate is not high enough for its practical application. In this paper, we proposed a Dual Temporal Scale Convolutional Neural Network (DTSCNN) for spontaneous micro-expressions recognition. The DTSCNN is a two-stream network. Different of stream of DTSCNN is used to adapt to different frame rate of micro-expression video clips. Each stream of DSTCNN consists of independent shallow network for avoiding the overfitting problem. Meanwhile, we fed the networks with optical-flow sequences to ensure that the shallow networks can further acquire higher-level features. Experimental results on spontaneous micro-expression databases (CASME I/II) showed that our method can achieve a recognition rate almost 10% higher than what some state-of-the-art method can achieve. PMID:29081753

Understanding the Properties of Interactive Televised Characters

Science.gov (United States)

Claxton, Laura J.; Ponto, Katelyn C.

2013-01-01

Children's television programming frequently uses interactive characters that appear to directly engage the viewers. These characters encourage children to answer questions and perform actions to help the characters solve problems in the televised world. Children readily engage in these interactions; however, it is unclear why they do so. To…

Document image retrieval through word shape coding.

Science.gov (United States)

Lu, Shijian; Li, Linlin; Tan, Chew Lim

2008-11-01

This paper presents a document retrieval technique that is capable of searching document images without OCR (optical character recognition). The proposed technique retrieves document images by a new word shape coding scheme, which captures the document content through annotating each word image by a word shape code. In particular, we annotate word images by using a set of topological shape features including character ascenders/descenders, character holes, and character water reservoirs. With the annotated word shape codes, document images can be retrieved by either query keywords or a query document image. Experimental results show that the proposed document image retrieval technique is fast, efficient, and tolerant to various types of document degradation.

Soumen Bag

Indian Academy of Sciences (India)

Home; Journals; Sadhana. Soumen Bag. Articles written in Sadhana. Volume 38 Issue 1 February 2013 pp 133-168. A survey on optical character recognition for Bangla and Devanagari scripts · Soumen Bag Gaurav Harit · More Details Abstract Fulltext PDF. The past few decades have witnessed an intensive research on ...

Study of the Effectiveness of OCR for Decentralized Data Capture and Conversion. Final Report.

Science.gov (United States)

Liston, David M.; And Others

The ERIC network conversion to an OCR (Optical Character Recognition) mode of data entry was studied to analyze the potential effectiveness of OCR data entry for future EPC/s (Editorial Processing Centers). Study results are also applicable to any other system involving decentralized bibliographic data capture and conversion functions. The report…

Information Science Research Institute quarterly progress report

Energy Technology Data Exchange (ETDEWEB)

Nartker, T.A.

1995-09-30

Subjects studied include optical character recognition (OCR), text retrieval, and document analysis. This report discusses the OCR test system and the text retrieval program. Staff and institute activities are given. Appendices give the ISRI methodology for preparing ground-truth test data and the test of OCR systems using DOE documents.

Optical computing and neural networks; Proceedings of the Meeting, National Chiao Tung Univ., Hsinchu, Taiwan, Dec. 16, 17, 1992

Science.gov (United States)

Hsu, Ken-Yuh (Editor); Liu, Hua-Kuang (Editor)

1992-01-01

The present conference discusses optical neural networks, photorefractive nonlinear optics, optical pattern recognition, digital and analog processors, and holography and its applications. Attention is given to bifurcating optical information processing, neural structures in digital halftoning, an exemplar-based optical neural net classifier for color pattern recognition, volume storage in photorefractive disks, and microlaser-based compact optical neuroprocessors. Also treated are the optical implementation of a feature-enhanced optical interpattern-associative neural network model and its optical implementation, an optical pattern binary dual-rail logic gate module, a theoretical analysis for holographic associative memories, joint transform correlators, image addition and subtraction via the Talbot effect, and optical wavelet-matched filters. (No individual items are abstracted in this volume)

Optical computing and neural networks; Proceedings of the Meeting, National Chiao Tung Univ., Hsinchu, Taiwan, Dec. 16, 17, 1992

Science.gov (United States)

Hsu, Ken-Yuh; Liu, Hua-Kuang

The present conference discusses optical neural networks, photorefractive nonlinear optics, optical pattern recognition, digital and analog processors, and holography and its applications. Attention is given to bifurcating optical information processing, neural structures in digital halftoning, an exemplar-based optical neural net classifier for color pattern recognition, volume storage in photorefractive disks, and microlaser-based compact optical neuroprocessors. Also treated are the optical implementation of a feature-enhanced optical interpattern-associative neural network model and its optical implementation, an optical pattern binary dual-rail logic gate module, a theoretical analysis for holographic associative memories, joint transform correlators, image addition and subtraction via the Talbot effect, and optical wavelet-matched filters. (No individual items are abstracted in this volume)

Femtosecond Non-Markovian Optical Dynamics in Solution

NARCIS (Netherlands)

Nibbering, Erik T.J.; Wiersma, Douwe A.; Duppen, Koos

1991-01-01

Femtosecond photon-echo experiments on sodium resorufin in dimethylsulfoxide at room temperature show that optical dephasing in solution is of non-Markovian character. A single Gauss-Markov stochastic modulation process is used to interpret both the femtosecond light-scattering results and the

Recognition of Handwriting from Electromyography

Science.gov (United States)

Linderman, Michael; Lebedev, Mikhail A.; Erlichman, Joseph S.

2009-01-01

Handwriting – one of the most important developments in human culture – is also a methodological tool in several scientific disciplines, most importantly handwriting recognition methods, graphology and medical diagnostics. Previous studies have relied largely on the analyses of handwritten traces or kinematic analysis of handwriting; whereas electromyographic (EMG) signals associated with handwriting have received little attention. Here we show for the first time, a method in which EMG signals generated by hand and forearm muscles during handwriting activity are reliably translated into both algorithm-generated handwriting traces and font characters using decoding algorithms. Our results demonstrate the feasibility of recreating handwriting solely from EMG signals – the finding that can be utilized in computer peripherals and myoelectric prosthetic devices. Moreover, this approach may provide a rapid and sensitive method for diagnosing a variety of neurogenerative diseases before other symptoms become clear. PMID:19707562

Factorized combinations of Virasoro characters

International Nuclear Information System (INIS)

Bytsko, A.G.; Fring, A.

2000-01-01

We investigate linear combinations of characters for minimal Virasoro models which are representable as a product of several basic blocks. Our analysis is based on consideration of asymptotic behaviour of the characters in the quasi-classical limit. In particular, we introduce a notion of the secondary effective central charge. We find all possible cases for which factorization occurs on the base of the Gauss-Jacobi or the Watson identities. Exploiting these results, we establish various types of identities between different characters. In particular, we present several identities generalizing the Rogers-Ramanujan identities. Applications to quasi-particle representations, modular invariant partition functions, super-conformal theories and conformal models with boundaries are briefly discussed. (orig.)

Retina image–based optic disc segmentation

Directory of Open Access Journals (Sweden)

Ching-Lin Wang

2016-05-01

Full Text Available The change of optic disc can be used to diagnose many eye diseases, such as glaucoma, diabetic retinopathy and macular degeneration. Moreover, retinal blood vessel pattern is unique for human beings even for identical twins. It is a highly stable pattern in biometric identification. Since optic disc is the beginning of the optic nerve and main blood vessels in retina, it can be used as a reference point of identification. Therefore, optic disc segmentation is an important technique for developing a human identity recognition system and eye disease diagnostic system. This article hence presents an optic disc segmentation method to extract the optic disc from a retina image. The experimental results show that the optic disc segmentation method can give impressive results in segmenting the optic disc from a retina image.

Advanced optical correlation and digital methods for pattern matching—50th anniversary of Vander Lugt matched filter

International Nuclear Information System (INIS)

Millán, María S

2012-01-01

On the verge of the 50th anniversary of Vander Lugt’s formulation for pattern matching based on matched filtering and optical correlation, we acknowledge the very intense research activity developed in the field of correlation-based pattern recognition during this period of time. The paper reviews some domains that appeared as emerging fields in the last years of the 20th century and have been developed later on in the 21st century. Such is the case of three-dimensional (3D) object recognition, biometric pattern matching, optical security and hybrid optical–digital processors. 3D object recognition is a challenging case of multidimensional image recognition because of its implications in the recognition of real-world objects independent of their perspective. Biometric recognition is essentially pattern recognition for which the personal identification is based on the authentication of a specific physiological characteristic possessed by the subject (e.g. fingerprint, face, iris, retina, and multifactor combinations). Biometric recognition often appears combined with encryption–decryption processes to secure information. The optical implementations of correlation-based pattern recognition processes still rely on the 4f-correlator, the joint transform correlator, or some of their variants. But the many applications developed in the field have been pushing the systems for a continuous improvement of their architectures and algorithms, thus leading towards merged optical–digital solutions. (review article)

The Effect of Pinyin Input Experience on the Link Between Semantic and Phonology of Chinese Character in Digital Writing.

Science.gov (United States)

Chen, Jingjun; Luo, Rong; Liu, Huashan

2017-08-01

With the development of ICT, digital writing is becoming much more common in people's life. Differently from keyboarding alphabets directly to input English words, keyboarding Chinese character is always through typing phonetic alphabets and then identify the glyph provided by Pinyin input-method software while in this process which do not need users to produce orthography spelling, thus it is different from traditional written language production model based on handwriting process. Much of the research in this domain has found that using Pinyin input method is beneficial to Chinese characters recognition, but only a small part explored the effects of individual's Pinyin input experience on the Chinese characters production process. We ask whether using Pinyin input-method will strengthen the semantic-phonology linkage or semantic-orthography linkage in Chinese character mental lexicon. Through recording the RT and accuracy of participants completing semantic-syllable and semantic-glyph consistency judgments, the results found the accuracy of semantic-syllable consistency judgments in high Pinyin input experienced group was higher than that in low-experienced group, and RT was reversed. There were no significant differences on semantic-glyph consistency judgments between the two groups. We conclude that using Pinyin input method in Chinese digital writing can strengthen the semantic-phonology linkage while do not weakening the semantic-orthography linkage in mental lexicon at the same time, which means that Pinyin input method is beneficial to lexical processing involving Chinese cognition.

Advances in image processing and pattern recognition. Proceedings of the international conference, Pisa, Italy, December 10-12, 1985

Energy Technology Data Exchange (ETDEWEB)

Cappellini, V [Florence Univ. (Italy); Consiglio Nazionale delle Ricerche, Florence (Italy). Ist. di Ricerca sulle Onde Elettromagnetiche); Marconi, R [IBM Scientific Center, Pisa (Italy); eds.

1986-01-01

The conference papers reported provide an authorative and permanent record of the contributions. Some papers are more theoretical or of review nature, while others contain new implementations and applications. They are conveniently grouped into the following 7 fields (after a general overview): Acquisition and Presentation of 2-D and 3-D Images; Static and Dynamic Image Processing; Determination of Object's Position and Orientation; Objects and Characters Recognition; Semantic Models and Image Understanding; Robotics and Computer Vision in Manufacturing; Specialized Processing Techniques and Structures. In particular, new digital image processing and recognition methods, implementation architectures and special advanced applications (industrial automation, robotics, remote sensing, biomedicine, etc.) are presented. (Auth.).

Good character at school: positive classroom behavior mediates the link between character strengths and school achievement.

Science.gov (United States)

Wagner, Lisa; Ruch, Willibald

2015-01-01

Character strengths have been found to be substantially related to children's and adolescents' well-being. Initial evidence suggests that they also matter for school success (e.g., Weber and Ruch, 2012). The present set of two studies aimed at replicating and extending these findings in two different age groups, primary school students (N = 179; mean age = 11.6 years) and secondary school students (N = 199; mean age = 14.4 years). The students completed the VIA-Youth (Values in Action Inventory of Strengths for Youth), a self-report measure of the 24 character strengths in the VIA classification. Their teachers rated the students' positive behavior in the classroom. Additionally, school achievement was assessed: For the primary school students (Study 1), teachers rated the students' overall school achievement and for the secondary school students (Study 2), we used their grades as a measure of school achievement. We found that several character strengths were associated with both positive classroom behavior and school achievement. Across both samples, school achievement was correlated with love of learning, perseverance, zest, gratitude, hope, and perspective. The strongest correlations with positive classroom behavior were found for perseverance, self-regulation, prudence, social intelligence, and hope. For both samples, there were indirect effects of some of the character strengths on school achievement through teacher-rated positive classroom behavior. The converging findings from the two samples support the notion that character strengths contribute to positive classroom behavior, which in turn enhances school achievement. Results are discussed in terms of their implications for future research and for school interventions based on character strengths.

Good character at school: Positive classroom behavior mediates the link between character strengths and school achievement

Directory of Open Access Journals (Sweden)

Lisa eWagner

2015-05-01

Full Text Available Character strengths have been found to be substantially related to children’s and adolescents’ well-being. Initial evidence suggests that they also matter for school success (e.g., Weber and Ruch, 2012. The present set of two studies aimed at replicating and extending these findings in two different age groups, primary school students (N = 179; mean age = 11.6 years and secondary school students (N = 199; mean age = 14.4 years. The students completed the VIA-Youth, a self-report measure of the 24 character strengths in the VIA classification. Their teachers rated the students’ positive behavior in the classroom. Additionally, school achievement was assessed: For the primary school students (Study 1, teachers rated the students’ overall school achievement and for the secondary school students (Study 2, we used their grades as a measure of school achievement. We found that several character strengths were associated with both positive classroom behavior and school achievement. Across both samples school achievement was correlated with love of learning, perseverance, zest, gratitude, hope, and perspective. The strongest correlations with positive classroom behavior were found for perseverance, self-regulation, prudence, social intelligence, and hope. For both samples, there were indirect effects of most of the character strengths on school achievement through teacher-rated positive classroom behavior. The converging findings from the two samples support the notion that character strengths contribute to positive classroom behavior, which in turn enhances school achievement. Results are discussed in terms of their implications for future research and for school interventions based on character strengths.

Antiaromatic bisindeno-[n]thienoacenes with small singlet biradical characters: Syntheses, structures and chain length dependent physical properties

KAUST Repository

Shi, Xueliang

2014-01-01

Recent studies demonstrated that aromaticity and biradical character play important roles in determining the ground-state structures and physical properties of quinoidal polycyclic hydrocarbons and oligothiophenes, a kind of molecular materials showing promising applications for organic electronics, photonics and spintronics. In this work, we designed and synthesized a new type of hybrid system, the so-called bisindeno-[n]thienoacenes (n = 1-4), by annulation of quinoidal fused α-oligothiophenes with two indene units. The obtained molecules can be regarded as antiaromatic systems containing 4n π electrons with small singlet biradical character (y0). Their ground-state geometry and electronic structures were studied by X-ray crystallographic analysis, NMR, ESR and Raman spectroscopy, assisted by density functional theory calculations. With extension of the chain length, the molecules showed a gradual increase of the singlet biradical character accompanied by decreased antiaromaticity, finally leading to a highly reactive bisindeno[4]thienoacene (S4-TIPS) which has a singlet biradical ground state (y0= 0.202). Their optical and electronic properties in the neutral and charged states were systematically investigated by one-photon absorption, two-photon absorption, transient absorption spectroscopy, cyclic voltammetry and spectroelectrochemistry, which could be correlated to the chain length dependent antiaromaticity and biradical character. Our detailed studies revealed a clear structure-aromaticity-biradical character-physical properties-reactivity relationship, which is of importance for tailored material design in the future. This journal is

On the information content of discrete phylogenetic characters.

Science.gov (United States)

Bordewich, Magnus; Deutschmann, Ina Maria; Fischer, Mareike; Kasbohm, Elisa; Semple, Charles; Steel, Mike

2017-12-16

Phylogenetic inference aims to reconstruct the evolutionary relationships of different species based on genetic (or other) data. Discrete characters are a particular type of data, which contain information on how the species should be grouped together. However, it has long been known that some characters contain more information than others. For instance, a character that assigns the same state to each species groups all of them together and so provides no insight into the relationships of the species considered. At the other extreme, a character that assigns a different state to each species also conveys no phylogenetic signal. In this manuscript, we study a natural combinatorial measure of the information content of an individual character and analyse properties of characters that provide the maximum phylogenetic information, particularly, the number of states such a character uses and how the different states have to be distributed among the species or taxa of the phylogenetic tree.

Comparison of confinement characters between porous silicon and silicon nanowires

International Nuclear Information System (INIS)

Tit, Nacir; Yamani, Zain H.; Pizzi, Giovanni; Virgilio, Michele

2011-01-01

Confinement character and its effects on photoluminescence (PL) properties are theoretically investigated and compared between porous silicon (p-Si) and silicon nanowires (Si-NWs). The method is based on the application of the tight-binding technique using the minimal sp 3 -basis set, including the second-nearest-neighbor interactions. The results show that the quantum confinement (QC) is not entirely controlled by the porosity, rather it is mainly affected by the average distance between pores (d). The p-Si is found to exhibit weaker confinement character than Si-NWs. The confinement energy of charge carriers decays against d exponentially for p-Si and via a power-law for Si-NWs. This latter type of QC is much stronger and is somewhat similar to the case of a single particle in a quantum box. The excellent fit to the PL data demonstrates that the experimental samples of p-Si do exhibit strong QC character and thus reveals the possibility of silicon clustering into nano-crystals and/or nanowires. Furthermore, the results show that the passivation of the surface dangling bonds by the hydrogen atoms plays an essential role in preventing the appearance of gap states and consequently enhances the optical qualities of the produced structures. The oscillator strength (OS) is found to increase exponentially with energy in Si-NWs confirming the strong confinement character of carriers. Our theoretical findings suggest the existence of Si nanocrystals (Si-NCs) of sizes 1-3 nm and/or Si-NWs of cross-sectional sizes in the 1-3 nm range inside the experimental p-Si samples. The experimentally-observed strong photoluminescence from p-Si should be in favor of an exhibition of 3D-confinement character. The favorable comparison of our theoretical results with the experimental data consolidates our above claims. -- Highlights: → Tight-binding is used to study quantum-confinement (QC) effects in p-Si and Si-NWs. → QC is not entirely controlled by the porosity but also by the d

Transfer Learning with Convolutional Neural Networks for SAR Ship Recognition

Science.gov (United States)

Zhang, Di; Liu, Jia; Heng, Wang; Ren, Kaijun; Song, Junqiang

2018-03-01

Ship recognition is the backbone of marine surveillance systems. Recent deep learning methods, e.g. Convolutional Neural Networks (CNNs), have shown high performance for optical images. Learning CNNs, however, requires a number of annotated samples to estimate numerous model parameters, which prevents its application to Synthetic Aperture Radar (SAR) images due to the limited annotated training samples. Transfer learning has been a promising technique for applications with limited data. To this end, a novel SAR ship recognition method based on CNNs with transfer learning has been developed. In this work, we firstly start with a CNNs model that has been trained in advance on Moving and Stationary Target Acquisition and Recognition (MSTAR) database. Next, based on the knowledge gained from this image recognition task, we fine-tune the CNNs on a new task to recognize three types of ships in the OpenSARShip database. The experimental results show that our proposed approach can obviously increase the recognition rate comparing with the result of merely applying CNNs. In addition, compared to existing methods, the proposed method proves to be very competitive and can learn discriminative features directly from training data instead of requiring pre-specification or pre-selection manually.

Which "Character" Should Sport Develop?

Science.gov (United States)

Rudd, Andy

2005-01-01

For years, strong claims have been made that sport builds character. Despite such claims, a "winning at all cost" mentality can frequently be seen within all of sport. The reason for this paradox may relate to confusion around what it means to demonstrate character. The purpose of this article is to show that there are indeed two distinct types of…

8 CFR 1292.2 - Organizations qualified for recognition; requests for recognition; withdrawal of recognition...

Science.gov (United States)

2010-01-01

...; requests for recognition; withdrawal of recognition; accreditation of representatives; roster. 1292.2...; requests for recognition; withdrawal of recognition; accreditation of representatives; roster. (a) Qualifications of organizations. A non-profit religious, charitable, social service, or similar organization...

Frontal view reconstruction for iris recognition

Science.gov (United States)

Santos-Villalobos, Hector J; Bolme, David S; Boehnen, Chris Bensing

2015-02-17

Iris recognition can be accomplished for a wide variety of eye images by correcting input images with an off-angle gaze. A variety of techniques, from limbus modeling, corneal refraction modeling, optical flows, and genetic algorithms can be used. A variety of techniques, including aspherical eye modeling, corneal refraction modeling, ray tracing, and the like can be employed. Precomputed transforms can enhance performance for use in commercial applications. With application of the technologies, images with significantly unfavorable gaze angles can be successfully recognized.

Recent progress in invariant pattern recognition

Science.gov (United States)

Arsenault, Henri H.; Chang, S.; Gagne, Philippe; Gualdron Gonzalez, Oscar

1996-12-01

We present some recent results in invariant pattern recognition, including methods that are invariant under two or more distortions of position, orientation and scale. There are now a few methods that yield good results under changes of both rotation and scale. Some new methods are introduced. These include locally adaptive nonlinear matched filters, scale-adapted wavelet transforms and invariant filters for disjoint noise. Methods using neural networks will also be discussed, including an optical method that allows simultaneous classification of multiple targets.

Threshold models of recognition and the recognition heuristic

Directory of Open Access Journals (Sweden)

Edgar Erdfelder

2011-02-01

Full Text Available According to the recognition heuristic (RH theory, decisions follow the recognition principle: Given a high validity of the recognition cue, people should prefer recognized choice options compared to unrecognized ones. Assuming that the memory strength of choice options is strongly correlated with both the choice criterion and recognition judgments, the RH is a reasonable strategy that approximates optimal decisions with a minimum of cognitive effort (Davis-Stober, Dana, and Budescu, 2010. However, theories of recognition memory are not generally compatible with this assumption. For example, some threshold models of recognition presume that recognition judgments can arise from two types of cognitive states: (1 certainty states in which judgments are almost perfectly correlated with memory strength and (2 uncertainty states in which recognition judgments reflect guessing rather than differences in memory strength. We report an experiment designed to test the prediction that the RH applies to certainty states only. Our results show that memory states rather than recognition judgments affect use of recognition information in binary decisions.

Pattern recognition in high energy physics

International Nuclear Information System (INIS)

Tenner, A.G.

1980-01-01

In high energy physics experiments tracks of elementary particles are recorded by different types of equipment. Coordinates of points of these tracks have to be measured for the geometrical reconstruction and the further analysis of the observed events. Pattern recognition methods may facilitate the detection of tracks or whole events and the separation of relevant from non-relevant information. They may also serve for the automation of measurement. Generally, all work is done by digital computation. In a bubble chamber tracks appear as strings of vapour bubbles that can be recorded photographically. Two methods of pattern recognition are discussed. The flying spot digitizer encodes the pattern on the photograph into point coordinates in the memory of a computer. The computer carries out the pattern recognition procedure entirely on the basis of the stored information. Cathode ray instruments scan the photograph by means of a computer steered optical device. Data acquisition from the film is performed in a feedback loop of the computation. In electronic experimental equipment tracks are defined by the spacial distribution of hits of counters (wire counters, scintillation counters, spark chambers). Pattern recognition is generally performed in various stages both by on-line and off-line equipment. Problems in the data handling arise both from the great abundance of data and from the time limits imposed on the on-line computation by high measuring rates. The on-line computation is carried out by hardwired logic, small computers, and to an increasing extent by microprocessors. (Auth.)

Template protection and its implementation in 3D face recognition systems

Science.gov (United States)

Zhou, Xuebing

2007-04-01

As biometric recognition systems are widely applied in various application areas, security and privacy risks have recently attracted the attention of the biometric community. Template protection techniques prevent stored reference data from revealing private biometric information and enhance the security of biometrics systems against attacks such as identity theft and cross matching. This paper concentrates on a template protection algorithm that merges methods from cryptography, error correction coding and biometrics. The key component of the algorithm is to convert biometric templates into binary vectors. It is shown that the binary vectors should be robust, uniformly distributed, statistically independent and collision-free so that authentication performance can be optimized and information leakage can be avoided. Depending on statistical character of the biometric template, different approaches for transforming biometric templates into compact binary vectors are presented. The proposed methods are integrated into a 3D face recognition system and tested on the 3D facial images of the FRGC database. It is shown that the resulting binary vectors provide an authentication performance that is similar to the original 3D face templates. A high security level is achieved with reasonable false acceptance and false rejection rates of the system, based on an efficient statistical analysis. The algorithm estimates the statistical character of biometric templates from a number of biometric samples in the enrollment database. For the FRGC 3D face database, the small distinction of robustness and discriminative power between the classification results under the assumption of uniquely distributed templates and the ones under the assumption of Gaussian distributed templates is shown in our tests.

THE CHARACTER ANALYSIS OF GLEN HANSARD IN ONCE FILM

Directory of Open Access Journals (Sweden)

Nani Rosnani Thamrin

2013-12-01

Full Text Available This paper analyzed the characterization of talented actor named Glen Hansard in Once film. This study employed a descriptive qualitative research design based on theories of Rahardjo (1985, Robert (1965, and Card (1988. Primary data sources were whole Once scenes film directed by John Carney which had low-budgeting production with two stars, Glen Hansard and Irglova, while secondary data sources were collected from the articles related to this study. This research mainly investigated two aspects involved two character analyses of the main actor, Hansard. The first one was the construction of Hansard’s characters and the second one was the effect between his character and another actors’ character. The study showed that Hansard’s characters were constructed by five factors: from what the character did and said, what the other characters said about him, how the appearance and its milieu were, influencing one and another.The study also found that he had struggle, visionary, ambitious, introvert, sensitive, straightforward and curious characters, but more characters that showed strong characters of his were struggle, visionary and ambitious, because the scenes reflected them more.

Functional and anatomical dissociation between the orthographic lexicon and the orthographic buffer revealed in reading and writing Chinese characters by fMRI.

Science.gov (United States)

Chen, Hsiang-Yu; Chang, Erik C; Chen, Sinead H Y; Lin, Yi-Chen; Wu, Denise H

2016-04-01

The contribution of orthographic representations to reading and writing has been intensively investigated in the literature. However, the distinction between neuronal correlates of the orthographic lexicon and the orthographic (graphemic) buffer has rarely been examined in alphabetic languages and never been explored in non-alphabetic languages. To determine whether the neural networks associated with the orthographic lexicon and buffer of logographic materials are comparable to those reported in the literature, the present fMRI experiment manipulated frequency and the stroke number of Chinese characters in the tasks of form judgment and stroke judgment, which emphasized the processing of character recognition and writing, respectively. It was found that the left fusiform gyrus exhibited higher activation when encountering low-frequency than high-frequency characters in both tasks, which suggested this region to be the locus of the orthographic lexicon that represents the knowledge of character forms. On the other hand, the activations in the posterior part of the left middle frontal gyrus and in the left angular gyrus were parametrically modulated by the stroke number of target characters only in the stroke judgment task, which suggested these regions to be the locus of the orthographic buffer that represents the processing of stroke sequence in writing. These results provide the first evidence for the functional and anatomical dissociation between the orthographic lexicon and buffer in reading and writing Chinese characters. They also demonstrate the critical roles of the left fusiform area and the frontoparietal network to the long-term and short-term representations of orthographic knowledge, respectively, across different orthographies. Copyright © 2016 Elsevier Inc. All rights reserved.

The character of free topological groups II

Directory of Open Access Journals (Sweden)

Peter Nickolas

2005-04-01

Full Text Available A systematic analysis is made of the character of the free and free abelian topological groups on metrizable spaces and compact spaces, and on certain other closely related spaces. In the first case, it is shown that the characters of the free and the free abelian topological groups on X are both equal to the “small cardinal” d if X is compact and metrizable, but also, more generally, if X is a non-discrete k!-space all of whose compact subsets are metrizable, or if X is a non-discrete Polish space. An example is given of a zero-dimensional separable metric space for which both characters are equal to the cardinal of the continuum. In the case of a compact space X, an explicit formula is derived for the character of the free topological group on X involving no cardinal invariant of X other than its weight; in particular the character is fully determined by the weight in the compact case. This paper is a sequel to a paper by the same authors in which the characters of the free groups were analysed under less restrictive topological assumptions.

Deep Classifiers-Based License Plate Detection, Localization and Recognition on GPU-Powered Mobile Platform

Directory of Open Access Journals (Sweden)

Syed Tahir Hussain Rizvi

2017-10-01

Full Text Available The realization of a deep neural architecture on a mobile platform is challenging, but can open up a number of possibilities for visual analysis applications. A neural network can be realized on a mobile platform by exploiting the computational power of the embedded GPU and simplifying the flow of a neural architecture trained on the desktop workstation or a GPU server. This paper presents an embedded platform-based Italian license plate detection and recognition system using deep neural classifiers. In this work, trained parameters of a highly precise automatic license plate recognition (ALPR system are imported and used to replicate the same neural classifiers on a Nvidia Shield K1 tablet. A CUDA-based framework is used to realize these neural networks. The flow of the trained architecture is simplified to perform the license plate recognition in real-time. Results show that the tasks of plate and character detection and localization can be performed in real-time on a mobile platform by simplifying the flow of the trained architecture. However, the accuracy of the simplified architecture would be decreased accordingly.

Application of the new pattern recognition system in the new e-nose to detecting Chinese spirits

International Nuclear Information System (INIS)

Gu Yu; Li Qiang

2014-01-01

We present a new pattern recognition system based on moving average and linear discriminant analysis (LDA), which can be used to process the original signal of the new polymer quartz piezoelectric crystal air-sensitive sensor system we designed, called the new e-nose. Using the new e-nose, we obtain the template datum of Chinese spirits via a new pattern recognition system. To verify the effectiveness of the new pattern recognition system, we select three kinds of Chinese spirits to test, our results confirm that the new pattern recognition system can perfectly identify and distinguish between the Chinese spirits. (electromagnetism, optics, acoustics, heat transfer, classical mechanics, and fluid dynamics)

DIALOGUE AND CHARACTER CLASSIFICATION IN WOLE ...

African Journals Online (AJOL)

position, level of education, character and habits of a character are reflected in the speech .... Dictators are averse to any form of ... breaks out shouting slogans of praises of himself. ..... Task easier if I can get all the Obas settled before our.

Aristotelian versus Virtue Ethical Character Education

Science.gov (United States)

Curren, Randall

2016-01-01

This article examines some central aspects of Kristján Kristjánsson's book, "Aristotelian Character Education," beginning with the claim that contemporary virtue ethics provides methodological, ontological, epistemological, and moral foundations for Aristotelian character education. It considers three different formulations of what…

A Review of Virtual Character's Emotion Model

Science.gov (United States)

Liu, Zhen

2008-11-01

Emotional virtual characters are essential to digital entertainment, an emotion is related to virtual environment and a virtual character's inner variables, emotion model of virtual character is a hot topic in many fields, domain knowledge is very important for modeling emotion, and the current research of emotion expression in the world was also summarized, and some new research directions of emotion model are presented.

Man Versus Machine: Comparing Double Data Entry and Optical Mark Recognition for Processing CAHPS Survey Data.

Science.gov (United States)

Fifolt, Matthew; Blackburn, Justin; Rhodes, David J; Gillespie, Shemeka; Bennett, Aleena; Wolff, Paul; Rucks, Andrew

Historically, double data entry (DDE) has been considered the criterion standard for minimizing data entry errors. However, previous studies considered data entry alternatives through the limited lens of data accuracy. This study supplies information regarding data accuracy, operational efficiency, and cost for DDE and Optical Mark Recognition (OMR) for processing the Consumer Assessment of Healthcare Providers and Systems 5.0 survey. To assess data accuracy, we compared error rates for DDE and OMR by dividing the number of surveys that were arbitrated by the total number of surveys processed for each method. To assess operational efficiency, we tallied the cost of data entry for DDE and OMR after survey receipt. Costs were calculated on the basis of personnel, depreciation for capital equipment, and costs of noncapital equipment. The cost savings attributed to this method were negated by the operational efficiency of OMR. There was a statistical significance between rates of arbitration between DDE and OMR; however, this statistical significance did not create a practical significance. The potential benefits of DDE in terms of data accuracy did not outweigh the operational efficiency and thereby financial savings of OMR.

The influence of media characters on children's food choices.

Science.gov (United States)

Kotler, Jennifer A; Schiffman, Jennifer M; Hanson, Katherine G

2012-01-01

Two experiments were conducted to assess the role of media characters in influencing children's food choices; the first focused on children's self-reported preference, whereas the second focused on actual choice. The results of the experiments suggest that popular characters can make a difference in encouraging children to select one food over another. In the first experiment, children were more likely to indicate a preference for one food over another when one was associated with characters that they liked and with whom they were familiar. This effect was particularly strong when a sugary or salty snack branded by a favored character was competing with a healthier option branded by an unknown character or no character. Alternatively, when children were asked to choose between a healthy food and a sugary or salty snack, branding of the healthy food with a favored character did not significantly change appeal of that healthy snack. However, when foods within the same category (i.e., 2 vegetables, 2 fruits, or 2 grains) were asked to compete against each other, character branding strongly influenced children's food choice. Findings from the second experiment suggest that children are more willing to try more pieces of a healthy food if a favored character, in comparison with an unknown character, is promoting that food.

Blunt Facial Trauma Causing Isolated Optic Nerve Hematoma

Directory of Open Access Journals (Sweden)

R. Parab

2013-01-01

Full Text Available Traumatic optic neuropathy is an uncommon, yet serious, result of facial trauma. The authors present a novel case of a 59-year-old gentleman who presented with an isolated blunt traumatic left optic nerve hematoma causing vision loss. There were no other injuries or fractures to report. This case highlights the importance of early recognition of this rare injury and reviews the current literature and management of traumatic optic neuropathy.

IFLA Section of Libraries for the Blind. Expert Meeting, 1984. Papers.

Science.gov (United States)

International Federation of Library Associations, The Hague (Netherlands).

Papers on library services and developments in reading materials for the blind, which were presented at the 1984 Expert Meeting of the IFLA Section of Libraries for the Blind include: (1) "Teaching Map Concepts to the Blind" (R. B. Horsfall and B. Cox, Canada); (2) "Optical Character Recognition 'Reading' for Computerized Braille Production"…

The Proximate Unit in Chinese Handwritten Character Production

Directory of Open Access Journals (Sweden)

Jenn-Yeu eChen

2013-08-01

Full Text Available In spoken word production, a proximate unit is the first phonological unit at the sublexical level that is selectable for production (O’Seaghdha, Chen, & Chen, 2010. The present study investigated whether the proximate unit in Chinese handwritten word production is the stroke, the radical, or something in between. A written version of the form preparation task was adopted. Chinese participants learned sets of two-character words, later were cued with the first character of each word, and had to write down the second character (the target. Response times were measured from the onset of a cue character to the onset of a written response. In Experiment 1, the target characters within a block shared (homogeneous or did not share (heterogeneous the first stroke. In Experiment 2, the first two strokes were shared in the homogeneous blocks. Response times in the homogeneous blocks and in the heterogeneous blocks were comparable in both experiments (Exp. 1: 687 ms vs. 684 ms, Exp. 2: 717 vs. 716. In Experiment 3 and 4, the target characters within a block shared or did not share the first radical. Response times in the homogeneous blocks were significantly faster than those in the heterogeneous blocks (Exp. 3: 685 vs. 704, Exp. 4: 594 vs. 650. In Experiment 5 and 6, the shared component was a Gestalt-like form that is more than a stroke, constitutes a portion of the target character, can be a stand-alone character itself, can be a radical of another character but is not a radical of the target character (e.g., 士in聲, 鼓, 穀, 款; called a logographeme. Response times in the homogeneous blocks were significantly faster than those in the heterogeneous blocks (Exp. 5: 576 vs. 625, Exp. 6: 586 vs. 620. These results suggest a model of Chinese handwritten character production in which the stroke is not a functional unit, the radical plays the role of a morpheme, and the logographeme is the proximate unit.

Dynamic Obstacle Clearing for Real-time Character Animation

OpenAIRE

Glardon, Pascal; Boulic, Ronan; Thalmann, Daniel

2006-01-01

This paper proposes a novel method to control virtual characters in dynamic environments. A virtual character is animated by a locomotion and jumping engine, enabling production of continuous parameterized motions. At any time during runtime, flat obstacles (e.g. a puddle of water) can be created and placed in front of a character. The method first decides whether the character is able to get around or jump over the obstacle. Then the motion parameters are accordingly modified. The transition...

Character feature integration of Chinese calligraphy and font

Science.gov (United States)

Shi, Cao; Xiao, Jianguo; Jia, Wenhua; Xu, Canhui

2013-01-01

A framework is proposed in this paper to effectively generate a new hybrid character type by means of integrating local contour feature of Chinese calligraphy with structural feature of font in computer system. To explore traditional art manifestation of calligraphy, multi-directional spatial filter is applied for local contour feature extraction. Then the contour of character image is divided into sub-images. The sub-images in the identical position from various characters are estimated by Gaussian distribution. According to its probability distribution, the dilation operator and erosion operator are designed to adjust the boundary of font image. And then new Chinese character images are generated which possess both contour feature of artistical calligraphy and elaborate structural feature of font. Experimental results demonstrate the new characters are visually acceptable, and the proposed framework is an effective and efficient strategy to automatically generate the new hybrid character of calligraphy and font.

Character education in perspective of chemistry pre-service teacher

Science.gov (United States)

Merdekawati, Krisna

2017-12-01

As one of the pre-service teacher education programs, Chemistry Education Department Islamic University of Indonesia (UII) is committed to providing quality education. It is an education that can produce competent and characteristic chemistry pre-service teacher. The focus of research is to describe the perception of students as a potential teacher of chemistry on character education and achievement of character education. The research instruments include questionnaires and observation sheets. Research data show that students have understood the importance of character education and committed to organizing character education later in schools. Students have understood the ways in which character education can be used. The students stated that Chemistry Education Department has tried to equip students with character education. The observation result shows that students generally have character as a pre-service teacher.

Vehicle license plate recognition in dense fog based on improved atmospheric scattering model

Science.gov (United States)

Tang, Chunming; Lin, Jun; Chen, Chunkai; Dong, Yancheng

2018-04-01

An effective method based on improved atmospheric scattering model is proposed in this paper to handle the problem of the vehicle license plate location and recognition in dense fog. Dense fog detection is performed firstly by the top-hat transformation and the vertical edge detection, and the moving vehicle image is separated from the traffic video image. After the vehicle image is decomposed into two layers: structure and texture layers, the glow layer is separated from the structure layer to get the background layer. Followed by performing the mean-pooling and the bicubic interpolation algorithm, the atmospheric light map of the background layer can be predicted, meanwhile the transmission of the background layer is estimated through the grayed glow layer, whose gray value is altered by linear mapping. Then, according to the improved atmospheric scattering model, the final restored image can be obtained by fusing the restored background layer and the optimized texture layer. License plate location is performed secondly by a series of morphological operations, connected domain analysis and various validations. Characters extraction is achieved according to the projection. Finally, an offline trained pattern classifier of hybrid discriminative restricted boltzmann machines (HDRBM) is applied to recognize the characters. Experimental results on thorough data sets are reported to demonstrate that the proposed method can achieve high recognition accuracy and works robustly in the dense fog traffic environment during 24h or one day.

Alterations in subspecific characters of groundnut

International Nuclear Information System (INIS)

Mouli, C.; Patil, S.H.; Kale, D.M.

1983-01-01

Recombination of beneficial characters associated in the cultivars of groundnut (Arachis hypogaea, L.) belonging to the two subspecies hypogaea and fastigiata had little success in conventional breeding programme. The cultures of ssp. hypogaea have the desirable characters for the crop improvement viz; various growth habits, profuse branching, large pod, seed dormancy and stress tolerance. Sequential flowering, early maturity, compact fruiting habit and high kernel outturn are the other useful characters present in ssp. fastigiata cultures. Mutation research in a popular variety, Spanish Improved belonging to ssp. fastigiata led to the selection of various mutants. One among the mutants had large pod, a characteristic of hypogaea ssp. Hybridization among the mutants and improved cultivars as well as radiation treatment of selected cultures resulted in the isolation of cultures having not only combinations and alterations of characters in both subspecies, but also modifications. These cultures are classified into major groups and their significance in the groundnut improvement is discussed. (author)

Character & Cane

Science.gov (United States)

Sartorius, Tara Cady

2009-01-01

They say first impressions can be deceiving. The difficulty of getting to know someone increases when that person is mostly fictional. Whatever the author writes is all readers can know. Whatever they read about the character is all they have to go on. Now take it another step back, and imagine a portrait drawing, painting or print of that…

Identification Of Minangkabau Landscape Characters

Science.gov (United States)

Asrina, M.; Gunawan, A.; Aris, Munandar

2017-10-01

Minangkabau is one of cultures in indonesia which occupies landscape intact. Landscape of Minangkabau have a very close relationship with the culture of the people. Uniqueness of Minangkabau culture and landscape forming an inseparable characterunity. The landscape is necessarily identified to know the inherent landscape characters. The objective of this study was to identify the character of the Minangkabau landscape characterizes its uniqueness. The study was conducted by using descriptive method comprised literature review and field observasion. Observed the landscape characters comprised two main features, they were major and minor features. Indetification of the features was conducted in two original areas (darek) of the Minangkabau traditional society. The research results showed that major features or natural features of the landscape were predominantly landform, landcover, and hidrology. All luhak (districts) of Minangkabau showed similar main features such as hill, canyon, lake, valley, and forest. The existence of natural features such as hills, canyon and valleys characterizes the nature of minangkabau landscape. Minor features formed by Minangkabau cultural society were agricultural land and settlement. Rumah gadang (big house) is one of famous minor features characterizes the Minangkabau culture. In addition, several historical artefacts of building and others structure may strengthen uniqueness of the Minangkabau landscape character, such as The royal palace, inscription, and tunnels.

Image processing and recognition for biological images.

Science.gov (United States)

Uchida, Seiichi

2013-05-01

This paper reviews image processing and pattern recognition techniques, which will be useful to analyze bioimages. Although this paper does not provide their technical details, it will be possible to grasp their main tasks and typical tools to handle the tasks. Image processing is a large research area to improve the visibility of an input image and acquire some valuable information from it. As the main tasks of image processing, this paper introduces gray-level transformation, binarization, image filtering, image segmentation, visual object tracking, optical flow and image registration. Image pattern recognition is the technique to classify an input image into one of the predefined classes and also has a large research area. This paper overviews its two main modules, that is, feature extraction module and classification module. Throughout the paper, it will be emphasized that bioimage is a very difficult target for even state-of-the-art image processing and pattern recognition techniques due to noises, deformations, etc. This paper is expected to be one tutorial guide to bridge biology and image processing researchers for their further collaboration to tackle such a difficult target. © 2013 The Author Development, Growth & Differentiation © 2013 Japanese Society of Developmental Biologists.

CHARACTER EDUCATION IN ISLAMIC BOARDING SCHOOL- BASED SMA AMANAH

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Nana Herdiana Abdurrahman

2016-06-01

Full Text Available This paper aims to describe findings of the study in pesantren-based SMA Amanah covering: 1 the principal policy in developing character education, 2 the methods used in developing character education, 3 students’ characteristics as the result of the character education process, 4 the problems encountered in the implementation of character education and the efforts made in addressing the implementation of character education at the school. This study applied qualitative method using descriptive technique. The data were collected through observation, interviews, and documentation. The findings of study showed that: 1 the principal’s policy in developing character education was carried out by implementing government policies in line with the school’s vision, mission, and programs; 2 the methods used in the process of character education were through role-modelling, assignments and nurturing, habituation, training programs, and  students’ participation in various types of activities, as well as the application of rewards and punishments; 3 the student's characteristics resulted from the character  education process were piousness and devotion as well as being able to apply their knowledge and piety in everyday life; 4 problems encountered in the implementation of character education  were different values and norms students brought from home; imbalance of facilities compared to the number of students; as well as teachers’ readiness to actually implement the new program, which  was character education. Meanwhile the efforts made to overcome those problems were namely developing personal, family, neighborhood or community characters, and making commitment of all related parties/stakeholdres of SMA Amanah.

Are we there yet?

Science.gov (United States)

Cristianini, Nello

2010-05-01

Statistical approaches to Artificial Intelligence are behind most success stories of the field in the past decade. The idea of generating non-trivial behaviour by analysing vast amounts of data has enabled recommendation systems, search engines, spam filters, optical character recognition, machine translation and speech recognition, among other things. As we celebrate the spectacular achievements of this line of research, we need to assess its full potential and its limitations. What are the next steps to take towards machine intelligence? 2010 Elsevier Ltd. All rights reserved.

Performance Measure as Feedback Variable in Image Processing

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Ristić Danijela

2006-01-01

Full Text Available This paper extends the view of image processing performance measure presenting the use of this measure as an actual value in a feedback structure. The idea behind is that the control loop, which is built in that way, drives the actual feedback value to a given set point. Since the performance measure depends explicitly on the application, the inclusion of feedback structures and choice of appropriate feedback variables are presented on example of optical character recognition in industrial application. Metrics for quantification of performance at different image processing levels are discussed. The issues that those metrics should address from both image processing and control point of view are considered. The performance measures of individual processing algorithms that form a character recognition system are determined with respect to the overall system performance.

Noisy Ocular Recognition Based on Three Convolutional Neural Networks

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Min Beom Lee

2017-12-01

Full Text Available In recent years, the iris recognition system has been gaining increasing acceptance for applications such as access control and smartphone security. When the images of the iris are obtained under unconstrained conditions, an issue of undermined quality is caused by optical and motion blur, off-angle view (the user’s eyes looking somewhere else, not into the front of the camera, specular reflection (SR and other factors. Such noisy iris images increase intra-individual variations and, as a result, reduce the accuracy of iris recognition. A typical iris recognition system requires a near-infrared (NIR illuminator along with an NIR camera, which are larger and more expensive than fingerprint recognition equipment. Hence, many studies have proposed methods of using iris images captured by a visible light camera without the need for an additional illuminator. In this research, we propose a new recognition method for noisy iris and ocular images by using one iris and two periocular regions, based on three convolutional neural networks (CNNs. Experiments were conducted by using the noisy iris challenge evaluation-part II (NICE.II training dataset (selected from the university of Beira iris (UBIRIS.v2 database, mobile iris challenge evaluation (MICHE database, and institute of automation of Chinese academy of sciences (CASIA-Iris-Distance database. As a result, the method proposed by this study outperformed previous methods.

Noisy Ocular Recognition Based on Three Convolutional Neural Networks.

Science.gov (United States)

Lee, Min Beom; Hong, Hyung Gil; Park, Kang Ryoung

2017-12-17

In recent years, the iris recognition system has been gaining increasing acceptance for applications such as access control and smartphone security. When the images of the iris are obtained under unconstrained conditions, an issue of undermined quality is caused by optical and motion blur, off-angle view (the user's eyes looking somewhere else, not into the front of the camera), specular reflection (SR) and other factors. Such noisy iris images increase intra-individual variations and, as a result, reduce the accuracy of iris recognition. A typical iris recognition system requires a near-infrared (NIR) illuminator along with an NIR camera, which are larger and more expensive than fingerprint recognition equipment. Hence, many studies have proposed methods of using iris images captured by a visible light camera without the need for an additional illuminator. In this research, we propose a new recognition method for noisy iris and ocular images by using one iris and two periocular regions, based on three convolutional neural networks (CNNs). Experiments were conducted by using the noisy iris challenge evaluation-part II (NICE.II) training dataset (selected from the university of Beira iris (UBIRIS).v2 database), mobile iris challenge evaluation (MICHE) database, and institute of automation of Chinese academy of sciences (CASIA)-Iris-Distance database. As a result, the method proposed by this study outperformed previous methods.

The location and recognition of anti-counterfeiting code image with complex background

Science.gov (United States)

Ni, Jing; Liu, Quan; Lou, Ping; Han, Ping

2017-07-01

The order of cigarette market is a key issue in the tobacco business system. The anti-counterfeiting code, as a kind of effective anti-counterfeiting technology, can identify counterfeit goods, and effectively maintain the normal order of market and consumers' rights and interests. There are complex backgrounds, light interference and other problems in the anti-counterfeiting code images obtained by the tobacco recognizer. To solve these problems, the paper proposes a locating method based on Susan operator, combined with sliding window and line scanning,. In order to reduce the interference of background and noise, we extract the red component of the image and convert the color image into gray image. For the confusing characters, recognition results correction based on the template matching method has been adopted to improve the recognition rate. In this method, the anti-counterfeiting code can be located and recognized correctly in the image with complex background. The experiment results show the effectiveness and feasibility of the approach.

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

Character and Characterization in “Palms and Men” novel

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Fariedeh Khajehpour

2013-11-01

Full Text Available Abstract Nowadays one of the most significant elements in story writing is character and characterization. Character in a narrative or a play, is a person that his mental and moral qualities reflect in his deeds and what he says and does. Creating such characters in a story or a novel that seem to be like real people to the reader is called characterization (Mir Sadeghi, 1382: p 85. In this article character and characterization in one of the novels about the eight year war between Iran and Iraq, calling “Palms and Men”, is investigated. Character types, methods of characterization, character appearance, prototype, the relation of character with other elements, and characterization defects are some of the subjects studied in this article.  Character types: these characters are generally categorized in two groups of stereotype and type. Samir, Touraj, Reza, Hamid etc. all belong to Sepah forces category which are type characters. Some women characters such as Zeinab, Samir’s mother, Kolsoum, Hanieh’s mother etc. are stereotype characters.   Methods of characterization in “Palms and Men” novel:   The description of characters is done in two methods by Mr. Nematollah Soleimani:   a Direct characterization: If not all the characters, most of them are certainly characterized in this way. For example in expressing Hamid’s characteristic who is the commander of the mission, he writes, “Hamid didn’t bat an eyelid in any incidents. Hamid was lion-hearted”. (Soleimani, 1380: 128. In describing uncle Heidar, he writes, “wisdom and insight, and the effects of years of suffering, difficulty, and experiencing could be clearly seen in his limpid eyes. The rural man was indeed a wise and experienced man” (the same: 264_265.   b Indirect Characterization: Although in novels and long stories, direct characterization method is often used, in “Palms and Men” this kind of characterization is also appeared in different conversations

Character and Characterization in “Palms and Men” novel

Directory of Open Access Journals (Sweden)

F. Khajeh pour

Full Text Available Nowadays one of the most significant elements in story writing is character and characterization. Character in a narrative or a play, is a person that his mental and moral qualities reflect in his deeds and what he says and does. Creating such characters in a story or a novel that seem to be like real people to the reader is called characterization (Mir Sadeghi, 1382: p 85. In this article character and characterization in one of the novels about the eight year war between Iran and Iraq, calling “Palms and Men”, is investigated. Character types, methods of characterization, character appearance, prototype, the relation of character with other elements, and characterization defects are some of the subjects studied in this article.Character types: these characters are generally categorized in two groups of stereotype and type. Samir, Touraj, Reza, Hamid etc. all belong to Sepah forces category which are type characters. Some women characters such as Zeinab, Samir’s mother, Kolsoum, Hanieh’s mother etc. are stereotype characters.Methods of characterization in “Palms and Men” novel:The description of characters is done in two methods by Mr. Nematollah Soleimani:aDirect characterization: If not all the characters, most of them are certainly characterized in this way. For example in expressing Hamid’s characteristic who is the commander of the mission, he writes, “Hamid didn’t bat an eyelid in any incidents. Hamid was lion-hearted”. (Soleimani, 1380: 128. In describing uncle Heidar, he writes, “wisdom and insight, and the effects of years of suffering, difficulty, and experiencing could be clearly seen in his limpid eyes. The rural man was indeed a wise and experienced man” (the same: 264_265.bIndirect Characterization: Although in novels and long stories, direct characterization method is often used, in “Palms and Men” this kind of characterization is also appeared in different conversations, stream of consciousness, deeds

WWC Evidence Review Protocol for Character Education Interventions

Science.gov (United States)

What Works Clearinghouse, 2014

2014-01-01

Character education is an inclusive concept regarding all aspects of how families, schools, and related social institutions support the positive character development of children and adults. "Character" in this context refers to the moral and ethical qualities of persons as well as the demonstration of those qualities in their emotional…

Improved document image segmentation algorithm using multiresolution morphology

Science.gov (United States)

Bukhari, Syed Saqib; Shafait, Faisal; Breuel, Thomas M.

2011-01-01

Page segmentation into text and non-text elements is an essential preprocessing step before optical character recognition (OCR) operation. In case of poor segmentation, an OCR classification engine produces garbage characters due to the presence of non-text elements. This paper describes modifications to the text/non-text segmentation algorithm presented by Bloomberg,1 which is also available in his open-source Leptonica library.2The modifications result in significant improvements and achieved better segmentation accuracy than the original algorithm for UW-III, UNLV, ICDAR 2009 page segmentation competition test images and circuit diagram datasets.

Rapid inventory taking system

International Nuclear Information System (INIS)

Marsden, P.S.S.F.

1980-01-01

A data processing system designed to facilitate inventory taking is described. The process depends upon the earliest possible application of computer techniques and the elimination of manual operations. Data is recorded in optical character recognition (OCR) 'A' form and read by a hand held wand reader. Limited validation checks are applied before recording on mini-tape cassettes. 5 refs

First Course in Japanese: Character Workbook.

Science.gov (United States)

Niwa, Tamako

This character workbook is an introduction to Japanese writing designed to be used in conjunction with Parts One and Two of this introductory course in Japanese. All the "hiragana", several "katakana", and 88 Japanese characters are introduced in this text. The workbook, consisting of 30 lessons, is divided into three parts.…

Do Rural Schools Need Character Education?

Science.gov (United States)

Reynolds, Janice Carner

Studies suggest that the challenge of violence in public schools can be met through character education, whether by providing a school culture in which core values are practiced or some form of moral training (indoctrination). To assess the need for character education in rural schools, small-school superintendents and board members in central…

Moral character predominates in person perception and evaluation.

Science.gov (United States)

Goodwin, Geoffrey P; Piazza, Jared; Rozin, Paul

2014-01-01

What sorts of trait information do people most care about when forming impressions of others? Recent research in social cognition suggests that "warmth," broadly construed, should be of prime importance in impression formation. Yet, some prior research suggests that information about others' specifically moral traits--their moral "character"--may be a primary dimension. Although warmth and character have sometimes been conceived of as interchangeable, we argue that they are separable, and that across a wide variety of contexts, character is usually more important than warmth in impression formation. We first showed that moral character and social warmth traits are indeed separable (Studies 1 and 2). Further studies that used correlational and experimental methods showed that, as predicted, in most contexts, moral character information is more important in impression formation than is warmth information (Studies 2-6). Character information was also more important than warmth information with respect to judgments of traits' perceived fundamentalness to identity, their uniquely human quality, their context-independence, and their controllability (Study 2). Finally, Study 7 used an archival method to show that moral character information appears more prominently than warmth information in obituaries, and more strongly determines the impressions people form of the individuals described in those obituaries. We discuss implications for current theories of person perception and social cognition.

Experimental Investigation of Integrated Optical Intensive Impulse Electric Field Sensors

International Nuclear Information System (INIS)

Bao, Sun; Fu-Shen, Chen

2009-01-01

We design and fabricate an integrated optical electric field sensor with segmented electrode for intensive impulse electric field measurement. The integrated optical sensor is based on a Mach–Zehnder interferometer with segmented electrodes. The output/input character of the sensing system is analysed and measured. The maximal detectable electric field range (−75 kV/m to 245 kV/m) is obtained by analysing the results. As a result, the integrated optics electric field sensing system is suitable for transient intensive electric field measurement investigation

Cultivating characters (moral value) through internalization strategy in science classroom

Science.gov (United States)

Ibrahim, M.; Abadi

2018-01-01

It is still in a crucial debate that characters play an important learning outcome to be realized by design. So far, most people think that characters were reached as nurturance effect with the assumption that students who are knowledgeable and skillful will have good characters automatically. Lately, obtained evidence that this assumption is not true. Characters should be taught deliberately or by design. This study was designed to culture elementary school students’ characters through science classroom. The teaching-learning process was conducted to facilitate and bridge the students from the known (concrete images: Science phenomena) to the unknown (abstract ideas: characters: care, and tolerance. Characters were observed five weeks before and after the intervention. Data were analyzed from observation of 24 students in internalization strategy-based courses. Qualitative and quantitative data suggested that the internalization strategy that use of science phenomena to represent abstract ideas (characters) in science classroom positively cultivating characters.

Character combinations, convergence and diversification in ectoparasitic arthropods.

Science.gov (United States)

Poulin, Robert

2009-08-01

Different lineages of organisms diversify over time at different rates, in part as a consequence of the characteristics of the species in these lineages. Certain suites of traits possessed by species within a clade may determine rates of diversification, with some particular combinations of characters acting synergistically to either limit or promote diversification; the most successful combinations may also emerge repeatedly in different clades via convergent evolution. Here, the association between species characters and diversification is investigated amongst 21 independent lineages of arthropods ectoparasitic on vertebrate hosts. Using nine characters (each with two to four states) that capture general life history strategy, transmission mode and host-parasite interaction, each lineage was described by the set of character states it possesses. The results show, firstly, that most possible pair-wise combinations of character states have been adopted at least once, sometimes several times independently by different lineages; thus, ectoparasitic arthropods have explored most of the life history character space available to them. Secondly, lineages possessing commonly observed combinations of character states are not necessarily the ones that have experienced the highest rates of diversification (measured as a clade's species-per-genus ratio). Thirdly, some specific traits are associated with higher rates of diversification. Using more than one host per generation, laying eggs away from the host and intermediate levels of fecundity are features that appear to have promoted diversification. These findings indicate that particular species characters may be evolutionary drivers of diversity, whose effects could also apply in other taxa.

The dark cube: dark and light character profiles

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Danilo Garcia

2016-02-01

Full Text Available Background. Research addressing distinctions and similarities between people’s malevolent character traits (i.e., the Dark Triad: Machiavellianism, narcissism, and psychopathy has detected inconsistent linear associations to temperament traits. Additionally, these dark traits seem to have a common core expressed as uncooperativeness. Hence, some researchers suggest that the dark traits are best represented as one global construct (i.e., the unification argument rather than as ternary construct (i.e., the uniqueness argument. We put forward the dark cube (cf. Cloninger’s character cube comprising eight dark profiles that can be used to compare individuals who differ in one dark character trait while holding the other two constant. Our aim was to investigate in which circumstances individuals who are high in each one of the dark character traits differ in Cloninger’s “light” character traits: self-directedness, cooperativeness, and self-transcendence. We also investigated if people’s dark character profiles were associated to their light character profiles. Method. A total of 997 participants recruited from Amazon’s Mechanical Turk (MTurk responded to the Short Dark Triad and the Short Character Inventory. Participants were allocated to eight different dark profiles and eight light profiles based on their scores in each of the traits and any possible combination of high and low scores. We used three-way interaction regression analyses and t-tests to investigate differences in light character traits between individuals with different dark profiles. As a second step, we compared the individuals’ dark profile with her/his character profile using an exact cell-wise analysis conducted in the ROPstat software (http://www.ropstat.com. Results. Individuals who expressed high levels of Machiavellianism and those who expressed high levels of psychopathy also expressed low self-directedness and low cooperativeness. Individuals with high

Skipping of Chinese characters does not rely on word-based processing.

Science.gov (United States)

Lin, Nan; Angele, Bernhard; Hua, Huimin; Shen, Wei; Zhou, Junyi; Li, Xingshan

2018-02-01

Previous eye-movement studies have indicated that people tend to skip extremely high-frequency words in sentence reading, such as "the" in English and "/de" in Chinese. Two alternative hypotheses have been proposed to explain how this frequent skipping happens in Chinese reading: one assumes that skipping happens when the preview has been fully identified at the word level (word-based skipping); the other assumes that skipping happens whenever the preview character is easy to identify regardless of whether lexical processing has been completed or not (character-based skipping). Using the gaze-contingent display change paradigm, we examined the two hypotheses by substituting the preview of the third character of a four-character Chinese word with the high-frequency Chinese character "/de", which should disrupt the ongoing word-level processing. The character-based skipping hypothesis predicts that this manipulation will enhance the skipping probability of the target character (i.e., the third character of the target word), because the character "/de" has much higher character frequency than the original character. The word-based skipping hypothesis instead predicts a reduction of the skipping probability of the target character because the presence of the character "/de" is lexically infelicitous at word level. The results supported the character-based skipping hypothesis, indicating that in Chinese reading the decision of skipping a character can be made before integrating it into a word.

Head capsule characters in the Hymenoptera and their phylogenetic implications

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Lars Vilhelmsen

2011-09-01

Full Text Available The head capsule of a taxon sample of three outgroup and 86 ingroup taxa is examined for characters of possible phylogenetic significance within Hymenoptera. 21 morphological characters are illustrated and scored, and their character evolution explored by mapping them onto a phylogeny recently produced from a large morphological data set. Many of the characters are informative and display unambiguous changes. Most of the character support demonstrated is supportive at the superfamily or family level. In contrast, only few characters corroborate deeper nodes in the phylogeny of Hymenoptera.

8 CFR 292.2 - Organizations qualified for recognition; requests for recognition; withdrawal of recognition...

Science.gov (United States)

2010-01-01

...; requests for recognition; withdrawal of recognition; accreditation of representatives; roster. 292.2...; withdrawal of recognition; accreditation of representatives; roster. (a) Qualifications of organizations. A non-profit religious, charitable, social service, or similar organization established in the United...

Submatrices of character tables and basic sets

DEFF Research Database (Denmark)

Bessenrodt, Christine; Olsson, Jørn Børling

2012-01-01

In this investigation of character tables of nite groups we study basic sets and associated representation theoretic data for complementary sets of conjugacy lasses. For the symmetric groups we nd unexpected properties of characters on restricted sets of conjugacy classes, like beautiful...... combinatorial determinant formulae for submatrices of the character table and Cartan matrices with respect to basic sets; we observe that similar phenomena occur for the transition matrices between power sum symmetric functions to bounded partitions and the k-Schur functions dened by Lapointe and Morse...

Visual Antipriming Effect: Evidence from Chinese Character Identification

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Feng Zhang

2017-10-01

Full Text Available Marsolek et al. (2006 have differentiated antipriming effects from priming effects, by adopting a novel priming paradigm comprised of four phases that include a baseline measurement. The general concept of antipriming supports the overlapping representation theory of knowledge. This study extended examination of the Marsolek et al. (2006 paradigm by investigating antipriming and priming effects in a series of Chinese character identification tasks. Results showed that identification accuracy of old characters was significantly higher than baseline measurements (i.e., the priming effect, while identification accuracy of novel characters was significantly lower than baseline measurements (i.e., the antipriming effect. This study demonstrates for the first time the effect of visual antipriming in Chinese character identification. It further provides new evidence for the overlapping representation theory of knowledge, and supports generalizability of the phenomenon to Chinese characters.

Character strengths, social anxiety, and physiological stress reactivity

Directory of Open Access Journals (Sweden)

Tingting Li

2017-05-01

Full Text Available In this paper, the effects of character strengths on the physiological reactivity to social anxiety induced by the Trier Social Stress Task were reported. On the basis of their scores in the Chinese Virtues Questionnaire, 30 college students were assigned to either high- (n = 15 or low-character-strength (n = 15 groups. Their psychological stress and physiological data across three laboratory stages (namely, baseline, stress exposure, and post-stress were collected. Results indicated that individuals with high character strengths exhibited rapid cardiovascular recovery from baseline to post-stress even if high- and low-character-strength groups showed similar patterns of cardiovascular arousal in response to the stress at baseline and stress exposure. These results prove that character strengths are stress-defense factors that allow for psychological and physiological adaptation to stress.

Representations of deaf characters in children's picture books.

Science.gov (United States)

Golos, Debbie B; Moses, Annie M

2011-01-01

Picture books can influence how children perceive people of different backgrounds, including people with disabilities whose cultures differ from their own. Researchers have examined the portrayal of multicultural characters with disabilities in children's literature. However, few have specifically considered the portrayal of deaf characters, despite increased inclusion of deaf characters in children's literature over the past two decades. The present study analyzed the portrayal of deaf characters in picture books for children ages 4-8 years. A content analysis of 20 children's picture books was conducted in which the books were analyzed for messages linked to pathological and cultural categories. Results indicated that these books did not portray Deaf characters from a cultural perspective but, rather, highlighted aspects of deafness as a medical condition, one that requires fixing and that perpetuates stereotypes of deafness as a disability.

Influence of a Character-Based App on Children's Learning of Nutritional Information: Should Apps Be Served with a Side of Media Characters?

Science.gov (United States)

Putnam, Marisa M; Richmond, Elana M; Brunick, Kaitlin L; Wright, Charlotte A; Calvert, Sandra L

2018-04-01

Childhood obesity is a health issue in the United States, associated with marketing practices in which media characters are often used to sell unhealthy products. This study examined exposure to a socially contingent touch-screen gaming app, which replied immediately, reliably, and accurately to children's actions. Children's recall of nutritional content and their liking of the character were assessed. Four- and five-year-old children (N = 114) received no-exposure, single-exposure, or repeated-exposure to a character-based iPad app rewarding healthy and penalizing unhealthy behaviors. Children reported how much they liked the character and recalled healthy and unhealthy items from the app. An ordinary least squares regression was conducted on how much children liked the character by condition. Poisson regressions were conducted on the number of items recalled by condition alone, and in an interacted model of treatment condition by liking the character. Children liked the character more in the repeated app-exposure condition than in the control group (P = 0.018). Children in the repeated and single app-exposure conditions recalled more healthy (P < 0.001) and unhealthy (P < 0.001) items than the control group. Within treatment conditions, liking the character increased recall of healthy items in the single app-exposure compared to the repeated app-exposure condition (P = 0.005). Results revealed that repeated exposure increased children's learning of nutritional information and liking of the character. The results contribute to our understanding of how to deliver effective nutrition information to young children in a new venue, a gaming app.

Optical stabilization for time transfer infrastructure

Science.gov (United States)

Vojtech, Josef; Altmann, Michal; Skoda, Pavel; Horvath, Tomas; Slapak, Martin; Smotlacha, Vladimir; Havlis, Ondrej; Munster, Petr; Radil, Jan; Kundrat, Jan; Altmannova, Lada; Velc, Radek; Hula, Miloslav; Vohnout, Rudolf

2017-08-01

In this paper, we propose and present verification of all-optical methods for stabilization of the end-to-end delay of an optical fiber link. These methods are verified for deployment within infrastructure for accurate time and stable frequency distribution, based on sharing of fibers with research and educational network carrying live data traffic. Methods range from path length control, through temperature conditioning method to transmit wavelength control. Attention is given to achieve continuous control for relatively broad range of delays. We summarize design rules for delay stabilization based on the character and the total delay jitter.

Modular initiator with integrated optical diagnostic

Science.gov (United States)

Alam, M Kathleen [Cedar Crest, NM; Schmitt, Randal L [Tijeras, NM; Welle, Eric J [Niceville, FL; Madden, Sean P [Arlington, MA

2011-05-17

A slapper detonator which integrally incorporates an optical wavequide structure for determining whether there has been degradation of the explosive in the explosive device that is to be initiated by the detonator. Embodiments of this invention take advantage of the barrel-like character of a typical slapper detonator design. The barrel assembly, being in direct contact with the energetic material, incorporates an optical diagnostic device into the barrel assembly whereby one can monitor the state of the explosive material. Such monitoring can be beneficial because the chemical degradation of the explosive plays an important in achieving proper functioning of a detonator/initiator device.

The Recognition of Overpass in Volunteered Geographic Information

Directory of Open Access Journals (Sweden)

MA Chao

2017-02-01

Full Text Available The paper presents an overpass recognition method in volunteered geographic information based on the geometry and attribute characteristics. The structure of the overpass is divided into the main bridge parts and the affiliated facilities. The main bridge parts with distinctive characters could be treated as a two-class classification problem. The characteristic vectors could build on the foundation of analysis and quantization the geometry and attribute characteristics. Then, the main bridge is recognized automatically through the support vector machine. The affiliated facilities of the overpass are recognized based on the main bridge with some relevant judgment rules. The OpenStreetMap(osm is selected for the experiment. The results show that the method could effectively recognize the overpass and could provide help for the road simplification and walking guidance.

Transient optical gain in germanium quantum wells

Energy Technology Data Exchange (ETDEWEB)

Chatterjee, Sangam; Lange, Christoph; Koester, Niko S.; Schaefer, Martin; Kira, Mackillo; Koch, Stephan W. [Faculty of Physics and Materials Sciences Center, Philipps-Universitaet Marburg (Germany); Chrastina, Daniel; Isella, Giovanni; Kaenel, Hans von [CNISM, Como (Italy); L-NESS, Dipartimento di Fisica del Politecnico di Milano, Como (Italy); Sigg, Hans [Laboratory for Micro and Nanotecnology, Paul Scherrer Institut, Villigen PSI (Switzerland)

2010-07-01

One of today's most-sought goals in semiconductor technology is the monolithic integration of microelectronics and photonics on Si. Optical gain is, in general, not expected for Si and Ge or its alloys due to the indirect nature of the band gap in this material system. Here, we show that Ge/SiGe QWs show transient optical gain and may thus be used as an optically-pumped amplifier at room temperature. Further, the nonequilibrium effects which govern the relaxation dynamics of the optically injected carrier distributions in this material were observed and analyzed using a microscopic many-body theory. Strong non-equilibrium gain was obtained on a sub-100 fs time scale. Long-lived gain arising from {gamma}-point transitions is overcompensated by a process bearing the character of free carrier absorption.

Pattern recognition in cyclic and discrete skills performance from inertial measurement units

NARCIS (Netherlands)

Seifert, Ludovic; L'Hermette, Maxime; Komar, John; Orth, Dominic; Mell, Florian; Merriaux, Pierre; Grenet, Pierre; Caritu, Yanis; Hérault, Romain; Dovgalecs, Vladislavs; Davids, Keith

2014-01-01

The aim of this study is to compare and validate an Inertial Measurement Unit (IMU) relative to an optic system, and to propose methods for pattern recognition to capture behavioural dynamics during sport performance. IMU validation was conducted by comparing the motions of the two arms of a

The Implementation of Character Education at Senior High School

Directory of Open Access Journals (Sweden)

Julia

2018-01-01

Full Text Available This paper is aimed at analyzing the implementation of character education at Senior High School in Sumedang Regency, West Java, Indonesia. A content analysis method was employed to collect the data with interviews with six teachers from six different senior high schools, which represent the rural, transitional, and urban areas. The findings revealed that: (1 not all teachers understand the concept of character education; (2 the character education has not been done systematically or has not had the specific design/model for the teaching and learning process. Most teachers embedded the character values during the teaching and learning process as a form of character education. For example, through Qur’an recitation, learning tasks, group discussion, lecture, socio-drama, observation and admonition, and even through teachers’ model. Meanwhile, outside the class, character education was implemented through competition and extracurricular activities; (3 the evaluation of character education was relatively varied, such as an observation followed by admonition, group guidance, and also focusing on behavior and affective assessment in the classroom learning process. This research implied that it is needed to make a policy on a program development through the Bureau of Education to improve Senior High School teachers’ knowledge and skills in implementing the character education.

A self-teaching image processing and voice-recognition-based, intelligent and interactive system to educate visually impaired children

Science.gov (United States)

Iqbal, Asim; Farooq, Umar; Mahmood, Hassan; Asad, Muhammad Usman; Khan, Akrama; Atiq, Hafiz Muhammad

2010-02-01

A self teaching image processing and voice recognition based system is developed to educate visually impaired children, chiefly in their primary education. System comprises of a computer, a vision camera, an ear speaker and a microphone. Camera, attached with the computer system is mounted on the ceiling opposite (on the required angle) to the desk on which the book is placed. Sample images and voices in the form of instructions and commands of English, Urdu alphabets, Numeric Digits, Operators and Shapes are already stored in the database. A blind child first reads the embossed character (object) with the help of fingers than he speaks the answer, name of the character, shape etc into the microphone. With the voice command of a blind child received by the microphone, image is taken by the camera which is processed by MATLAB® program developed with the help of Image Acquisition and Image processing toolbox and generates a response or required set of instructions to child via ear speaker, resulting in self education of a visually impaired child. Speech recognition program is also developed in MATLAB® with the help of Data Acquisition and Signal Processing toolbox which records and process the command of the blind child.

Detection and recognition of mechanical, digging and vehicle signals in the optical fiber pre-warning system

Science.gov (United States)

Tian, Qing; Yang, Dan; Zhang, Yuan; Qu, Hongquan

2018-04-01

This paper presents detection and recognition method to locate and identify harmful intrusions in the optical fiber pre-warning system (OFPS). Inspired by visual attention architecture (VAA), the process flow is divided into two parts, i.e., data-driven process and task-driven process. At first, data-driven process takes all the measurements collected by the system as input signals, which is handled by detection method to locate the harmful intrusion in both spatial domain and time domain. Then, these detected intrusion signals are taken over by task-driven process. Specifically, we get pitch period (PP) and duty cycle (DC) of the intrusion signals to identify the mechanical and manual digging (MD) intrusions respectively. For the passing vehicle (PV) intrusions, their strong low frequency component can be used as good feature. In generally, since the harmful intrusion signals only account for a small part of whole measurements, the data-driven process reduces the amount of input data for subsequent task-driven process considerably. Furthermore, the task-driven process determines the harmful intrusions orderly according to their severity, which makes a priority mechanism for the system as well as targeted processing for different harmful intrusion. At last, real experiments are performed to validate the effectiveness of this method.

The Inaccuracy of National Character Stereotypes

Science.gov (United States)

McCrae, Robert R.; Chan, Wayne; Jussim, Lee; De Fruyt, Filip; Löckenhoff, Corinna E.; De Bolle, Marleen; Costa, Paul T.; Hřebíčková, Martina; Graf, Sylvie; Realo, Anu; Allik, Jüri; Nakazato, Katsuharu; Shimonaka, Yoshiko; Yik, Michelle; Ficková, Emília; Brunner-Sciarra, Marina; Reátigui, Norma; de Figueora, Nora Leibovich; Schmidt, Vanina; Ahn, Chang-kyu; Ahn, Hyun-nie; Aguilar-Vafaie, Maria E.; Siuta, Jerzy; Szmigielska, Barbara; Cain, Thomas R.; Crawford, Jarret T.; Mastor, Khairul Anwar; Rolland, Jean-Pierre; Nansubuga, Florence; Miramontez, Daniel R.; Benet-Martínez, Veronica; Rossier, Jérôme; Bratko, Denis; Marušić, Iris; Halberstadt, Jamin; Yamaguchi, Mami; Knežević, Goran; Purić, Danka; Martin, Thomas A.; Gheorghiu, Mirona; Smith, Peter B.; Barbaranelli, Claudio; Wang, Lei; Shakespeare-Finch, Jane; Lima, Margarida P.; Klinkosz, Waldemar; Sekowski, Andrzej; Alcalay, Lidia; Simonetti, Franco; Avdeyeva, Tatyana V.; Pramila, V. S.; Terracciano, Antonio

2013-01-01

Consensual stereotypes of some groups are relatively accurate, whereas others are not. Previous work suggesting that national character stereotypes are inaccurate has been criticized on several grounds. In this article we (a) provide arguments for the validity of assessed national mean trait levels as criteria for evaluating stereotype accuracy; and (b) report new data on national character in 26 cultures from descriptions (N=3,323) of the typical male or female adolescent, adult, or old person in each. The average ratings were internally consistent and converged with independent stereotypes of the typical culture member, but were weakly related to objective assessments of personality. We argue that this conclusion is consistent with the broader literature on the inaccuracy of national character stereotypes. PMID:24187394

Transliterating non-ASCII characters with Python

Directory of Open Access Journals (Sweden)

Seth Bernstein

2013-10-01

Full Text Available This lesson shows how to use Python to transliterate automatically a list of words from a language with a non-Latin alphabet to a standardized format using the American Standard Code for Information Interchange (ASCII characters. It builds on readers’ understanding of Python from the lessons “Viewing HTML Files,” “Working with Web Pages,” “From HTML to List of Words (part 1” and “Intro to Beautiful Soup.” At the end of the lesson, we will use the transliteration dictionary to convert the names from a database of the Russian organization Memorial from Cyrillic into Latin characters. Although the example uses Cyrillic characters, the technique can be reproduced with other alphabets using Unicode.

Animated Character Analysis and Costume Design with Structured Analysis

OpenAIRE

Yıldırım Artaç, Berna; Ağaç, Saliha

2016-01-01

In various genres, costumes complement fictional characters and not onlyconstitute the external appearance of the fictional character, but are alsoused for purposes of fun or style by fans who dress up as the character andinternalize that character’s state of mind. This phenomenon is calledcosplay. A literature review of the field has revealed no study made previouslyon the cosplay costume design process according to character analysis. Thepresent study emphasizes the link between an...

A method of vehicle license plate recognition based on PCANet and compressive sensing

Science.gov (United States)

Ye, Xianyi; Min, Feng

2018-03-01

The manual feature extraction of the traditional method for vehicle license plates has no good robustness to change in diversity. And the high feature dimension that is extracted with Principal Component Analysis Network (PCANet) leads to low classification efficiency. For solving these problems, a method of vehicle license plate recognition based on PCANet and compressive sensing is proposed. First, PCANet is used to extract the feature from the images of characters. And then, the sparse measurement matrix which is a very sparse matrix and consistent with Restricted Isometry Property (RIP) condition of the compressed sensing is used to reduce the dimensions of extracted features. Finally, the Support Vector Machine (SVM) is used to train and recognize the features whose dimension has been reduced. Experimental results demonstrate that the proposed method has better performance than Convolutional Neural Network (CNN) in the recognition and time. Compared with no compression sensing, the proposed method has lower feature dimension for the increase of efficiency.

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

The genetic and environmental structure of the character sub-scales of the temperament and character inventory in adolescence.

Science.gov (United States)

Lester, Nigel; Garcia, Danilo; Lundström, Sebastian; Brändström, Sven; Råstam, Maria; Kerekes, Nóra; Nilsson, Thomas; Cloninger, C Robert; Anckarsäter, Henrik

2016-01-01

The character higher order scales (self-directedness, cooperativeness, and self-transcendence) in the temperament and character inventory are important general measures of health and well-being [Mens Sana Monograph 11:16-24 (2013)]. Recent research has found suggestive evidence of common environmental influence on the development of these character traits during adolescence. The present article expands earlier research by focusing on the internal consistency and the etiology of traits measured by the lower order sub-scales of the character traits in adolescence. The twin modeling analysis of 423 monozygotic pairs and 408 same sex dizygotic pairs estimated additive genetics (A), common environmental (C), and non-shared environmental (E) influences on twin resemblance. All twins were part of the on-going longitudinal Child and Adolescent Twin Study in Sweden (CATSS). The twin modeling analysis suggested a common environmental contribution for two out of five self-directedness sub-scales (0.14 and 0.23), for three out of five cooperativeness sub-scales (0.07-0.17), and for all three self-transcendence sub-scales (0.10-0.12). The genetic structure at the level of the character lower order sub-scales in adolescents shows that the proportion of the shared environmental component varies in the trait of self-directedness and in the trait of cooperativeness, while it is relatively stable across the components of self-transcendence. The presence of this unique shared environmental effect in adolescence has implications for understanding the relative importance of interventions and treatment strategies aimed at promoting overall maturation of character, mental health, and well-being during this period of the life span.

How jurors use and misuse character evidence.

Science.gov (United States)

Hunt, Jennifer S; Budesheim, Thomas Lee

2004-04-01

The Federal Rules of Evidence allow defendants to offer testimony about their good character, but that testimony can be impeached with cross-examination or a rebuttal witness. It is assumed that jurors use the defense's character evidence (CE) to form guilt and conviction judgments but use impeachment evidence only to assess the character witness's credibility. Two experiments tested these assumptions by presenting mock jurors with various forms of CE and impeachment. Participants made trait ratings for the character witness and defendant and guilt and conviction judgments. Positive CE did not affect guilt or conviction judgments, but cross-examination caused a backlash in which judgments were harsher than when no CE was given. Using path analysis, the authors tested a model of the process by which CE and impeachment affect defendant and witness impressions and guilt and conviction judgments. Implications for juror decision making are discussed.

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

High-speed cell recognition algorithm for ultrafast flow cytometer imaging system

Science.gov (United States)

Zhao, Wanyue; Wang, Chao; Chen, Hongwei; Chen, Minghua; Yang, Sigang

2018-04-01

An optical time-stretch flow imaging system enables high-throughput examination of cells/particles with unprecedented high speed and resolution. A significant amount of raw image data is produced. A high-speed cell recognition algorithm is, therefore, highly demanded to analyze large amounts of data efficiently. A high-speed cell recognition algorithm consisting of two-stage cascaded detection and Gaussian mixture model (GMM) classification is proposed. The first stage of detection extracts cell regions. The second stage integrates distance transform and the watershed algorithm to separate clustered cells. Finally, the cells detected are classified by GMM. We compared the performance of our algorithm with support vector machine. Results show that our algorithm increases the running speed by over 150% without sacrificing the recognition accuracy. This algorithm provides a promising solution for high-throughput and automated cell imaging and classification in the ultrafast flow cytometer imaging platform.

Technical guide for monitoring selected conditions related to wilderness character

Science.gov (United States)

Peter Landres; Steve Boutcher; Liese Dean; Troy Hall; Tamara Blett; Terry Carlson; Ann Mebane; Carol Hardy; Susan Rinehart; Linda Merigliano; David N. Cole; Andy Leach; Pam Wright; Deb Bumpus

2009-01-01

The purpose of monitoring wilderness character is to improve wilderness stewardship by providing managers a tool to assess how selected actions and conditions related to wilderness character are changing over time. Wilderness character monitoring provides information to help answer two key questions about wilderness character and wilderness stewardship: 1. How is...

Compact optical processor for Hough and frequency domain features

Science.gov (United States)

Ott, Peter

1996-11-01

Shape recognition is necessary in a broad band of applications such as traffic sign or work piece recognition. It requires not only neighborhood processing of the input image pixels but global interconnection of them. The Hough transform (HT) performs such a global operation and it is well suited in the preprocessing stage of a shape recognition system. Translation invariant features can be easily calculated form the Hough domain. We have implemented on the computer a neural network shape recognition system which contains a HT, a feature extraction, and a classification layer. The advantage of this approach is that the total system can be optimized with well-known learning techniques and that it can explore the parallelism of the algorithms. However, the HT is a time consuming operation. Parallel, optical processing is therefore advantageous. Several systems have been proposed, based on space multiplexing with arrays of holograms and CGH's or time multiplexing with acousto-optic processors or by image rotation with incoherent and coherent astigmatic optical processors. We took up the last mentioned approach because 2D array detectors are read out line by line, so a 2D detector can achieve the same speed and is easier to implement. Coherent processing can allow the implementation of tilers in the frequency domain. Features based on wedge/ring, Gabor, or wavelet filters have been proven to show good discrimination capabilities for texture and shape recognition. The astigmatic lens system which is derived form the mathematical formulation of the HT is long and contains a non-standard, astigmatic element. By methods of lens transformation s for coherent applications we map the original design to a shorter lens with a smaller number of well separated standard elements and with the same coherent system response. The final lens design still contains the frequency plane for filtering and ray-tracing shows diffraction limited performance. Image rotation can be done

Real-time image restoration for iris recognition systems.

Science.gov (United States)

Kang, Byung Jun; Park, Kang Ryoung

2007-12-01

In the field of biometrics, it has been reported that iris recognition techniques have shown high levels of accuracy because unique patterns of the human iris, which has very many degrees of freedom, are used. However, because conventional iris cameras have small depth-of-field (DOF) areas, input iris images can easily be blurred, which can lead to lower recognition performance, since iris patterns are transformed by the blurring caused by optical defocusing. To overcome these problems, an autofocusing camera can be used. However, this inevitably increases the cost, size, and complexity of the system. Therefore, we propose a new real-time iris image-restoration method, which can increase the camera's DOF without requiring any additional hardware. This paper presents five novelties as compared to previous works: 1) by excluding eyelash and eyelid regions, it is possible to obtain more accurate focus scores from input iris images; 2) the parameter of the point spread function (PSF) can be estimated in terms of camera optics and measured focus scores; therefore, parameter estimation is more accurate than it has been in previous research; 3) because the PSF parameter can be obtained by using a predetermined equation, iris image restoration can be done in real-time; 4) by using a constrained least square (CLS) restoration filter that considers noise, performance can be greatly enhanced; and 5) restoration accuracy can also be enhanced by estimating the weight value of the noise-regularization term of the CLS filter according to the amount of image blurring. Experimental results showed that iris recognition errors when using the proposed restoration method were greatly reduced as compared to those results achieved without restoration or those achieved using previous iris-restoration methods.

Thresholding: A Pixel-Level Image Processing Methodology Preprocessing Technique for an OCR System for the Brahmi Script

Directory of Open Access Journals (Sweden)

H. K. Anasuya Devi

2006-12-01

Full Text Available In this paper we study the methodology employed for preprocessing the archaeological images. We present the various algorithms used in the low-level processing stage of image analysis for Optical Character Recognition System for Brahmi Script. The image preprocessing technique covered in this paper is thresholding. We also try to analyze the results obtained by the pixel-level processing algorithms.

Polarization control of non-diffractive helical optical beams through subwavelength metallic apertures

International Nuclear Information System (INIS)

Lombard, E; Genet, C; Ebbesen, T W; Drezet, A

2010-01-01

We demonstrate experimentally a simple method for preparing non-diffractive vectorial optical beams that can display wave-front helicity. This method is based on space-variant modifications of the polarization of an optical beam transmitted through subwavelength annular rings perforating opaque metal films. We show how the description of the optical properties of such structures must account for the vectorial character of the polarization and how, in turn, these properties can be controlled by straightforward sequences of preparation and analysis of polarization states.

Effect of refractive error on temperament and character properties

Institute of Scientific and Technical Information of China (English)

Emine; Kalkan; Akcay; Fatih; Canan; Huseyin; Simavli; Derya; Dal; Hacer; Yalniz; Nagihan; Ugurlu; Omer; Gecici; Nurullah; Cagil

2015-01-01

AIM: To determine the effect of refractive error on temperament and character properties using Cloninger’s psychobiological model of personality.METHODS: Using the Temperament and Character Inventory(TCI), the temperament and character profiles of 41 participants with refractive errors(17 with myopia,12 with hyperopia, and 12 with myopic astigmatism) were compared to those of 30 healthy control participants.Here, temperament comprised the traits of novelty seeking, harm-avoidance, and reward dependence, while character comprised traits of self-directedness,cooperativeness, and self-transcendence.RESULTS: Participants with refractive error showed significantly lower scores on purposefulness,cooperativeness, empathy, helpfulness, and compassion(P <0.05, P <0.01, P <0.05, P <0.05, and P <0.01,respectively).CONCLUSION: Refractive error might have a negative influence on some character traits, and different types of refractive error might have different temperament and character properties. These personality traits may be implicated in the onset and/or perpetuation of refractive errors and may be a productive focus for psychotherapy.