WorldWideScience

Sample records for handwritten digit recognition

  1. 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.

  2. Classification and recognition of handwritten digits by using ...

    Indian Academy of Sciences (India)

    exploit the technology for digit recognition. Haralick & Kanungo (1990) presented their par- tially completed work of character recognition using mathematical morphology. The basic operations of erosion and dilation are discussed in Haralick & Kanungo (1990) and their applications to recognize six out of ten handwritten ...

  3. A Study of Moment Based Features on Handwritten Digit Recognition

    Directory of Open Access Journals (Sweden)

    Pawan Kumar Singh

    2016-01-01

    Full Text Available Handwritten digit recognition plays a significant role in many user authentication applications in the modern world. As the handwritten digits are not of the same size, thickness, style, and orientation, therefore, these challenges are to be faced to resolve this problem. A lot of work has been done for various non-Indic scripts particularly, in case of Roman, but, in case of Indic scripts, the research is limited. This paper presents a script invariant handwritten digit recognition system for identifying digits written in five popular scripts of Indian subcontinent, namely, Indo-Arabic, Bangla, Devanagari, Roman, and Telugu. A 130-element feature set which is basically a combination of six different types of moments, namely, geometric moment, moment invariant, affine moment invariant, Legendre moment, Zernike moment, and complex moment, has been estimated for each digit sample. Finally, the technique is evaluated on CMATER and MNIST databases using multiple classifiers and, after performing statistical significance tests, it is observed that Multilayer Perceptron (MLP classifier outperforms the others. Satisfactory recognition accuracies are attained for all the five mentioned scripts.

  4. Arabic Handwritten Digit Recognition Based on Restricted Boltzmann Machine and Convolutional Neural Networks

    Directory of Open Access Journals (Sweden)

    Ali A. Alani

    2017-11-01

    Full Text Available Handwritten digit recognition is an open problem in computer vision and pattern recognition, and solving this problem has elicited increasing interest. The main challenge of this problem is the design of an efficient method that can recognize the handwritten digits that are submitted by the user via digital devices. Numerous studies have been proposed in the past and in recent years to improve handwritten digit recognition in various languages. Research on handwritten digit recognition in Arabic is limited. At present, deep learning algorithms are extremely popular in computer vision and are used to solve and address important problems, such as image classification, natural language processing, and speech recognition, to provide computers with sensory capabilities that reach the ability of humans. In this study, we propose a new approach for Arabic handwritten digit recognition by use of restricted Boltzmann machine (RBM and convolutional neural network (CNN deep learning algorithms. In particular, we propose an Arabic handwritten digit recognition approach that works in two phases. First, we use the RBM, which is a deep learning technique that can extract highly useful features from raw data, and which has been utilized in several classification problems as a feature extraction technique in the feature extraction phase. Then, the extracted features are fed to an efficient CNN architecture with a deep supervised learning architecture for the training and testing process. In the experiment, we used the CMATERDB 3.3.1 Arabic handwritten digit dataset for training and testing the proposed method. Experimental results show that the proposed method significantly improves the accuracy rate, with accuracy reaching 98.59%. Finally, comparison of our results with those of other studies on the CMATERDB 3.3.1 Arabic handwritten digit dataset shows that our approach achieves the highest accuracy rate.

  5. Multi-Digit Handwritten Sindhi Numerals Recognition using SOM Neural Network

    Directory of Open Access Journals (Sweden)

    ASGHAR ALI CHANDIO

    2017-10-01

    Full Text Available 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.

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

    Science.gov (United States)

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

    2016-08-01

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

  7. DATABASES FOR RECOGNITION OF HANDWRITTEN ARABIC CHEQUES

    NARCIS (Netherlands)

    Alohali, Y.; Cheriet, M.; Suen, C.Y.

    2004-01-01

    This paper describes an effort toward building Arabic cheque databases for research in recognition of handwritten Arabic cheques. Databases of Arabic legal amounts, Arabic sub­ words, courtesy amounts, Indian digits, and Arabic cheques are provided. This paper highlights the characteristics of the

  8. Handwritten Arabic Numeral Recognition using a Multi Layer Perceptron

    OpenAIRE

    Das, Nibaran; Mollah, Ayatullah Faruk; Saha, Sudip; Haque, Syed Sahidul

    2010-01-01

    Handwritten numeral recognition is in general a benchmark problem of Pattern Recognition and Artificial Intelligence. Compared to the problem of printed numeral recognition, the problem of handwritten numeral recognition is compounded due to variations in shapes and sizes of handwritten characters. Considering all these, the problem of handwritten numeral recognition is addressed under the present work in respect to handwritten Arabic numerals. Arabic is spoken throughout the Arab World and t...

  9. New efficient algorithm for recognizing handwritten Hindi digits

    Science.gov (United States)

    El-Sonbaty, Yasser; Ismail, Mohammed A.; Karoui, Kamal

    2001-12-01

    In this paper a new algorithm for recognizing handwritten Hindi digits is proposed. The proposed algorithm is based on using the topological characteristics combined with statistical properties of the given digits in order to extract a set of features that can be used in the process of digit classification. 10,000 handwritten digits are used in the experimental results. 1100 digits are used for training and another 5500 unseen digits are used for testing. The recognition rate has reached 97.56%, a substitution rate of 1.822%, and a rejection rate of 0.618%.

  10. Post processing for offline Chinese handwritten character string recognition

    Science.gov (United States)

    Wang, YanWei; Ding, XiaoQing; Liu, ChangSong

    2012-01-01

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

  11. RECOGNITION AND VERIFICATION OF TOUCHING HANDWRITTEN NUMERALS

    NARCIS (Netherlands)

    Zhou, J.; Kryzak, A.; Suen, C.Y.

    2004-01-01

    In the field of financial document processing, recognition of touching handwritten numerals has been limited by lack of good benchmarking databases and low reliability of algorithms. This paper addresses the efforts toward solving the two problems. Two databases IRIS-Bell\\\\\\'98 and TNIST are

  12. A Comparison of Feature and Pixel-Based Methods for Recognizing Handwritten Bangla Digits

    NARCIS (Netherlands)

    Surinta, Olarik; Schomaker, Lambertus; Wiering, Marco

    2013-01-01

    We propose a novel handwritten character recognition method for isolated handwritten Bangla digits. A feature is introduced for such patterns, the contour angular technique. It is compared to other methods, such as the hotspot feature, the gray-level normalized character image and a basic

  13. On the Optimum Architecture of the Biologically Inspired Hierarchical Temporal Memory Model Applied to the Hand-Written Digit Recognition

    Science.gov (United States)

    Štolc, Svorad; Bajla, Ivan

    2010-01-01

    In the paper we describe basic functions of the Hierarchical Temporal Memory (HTM) network based on a novel biologically inspired model of the large-scale structure of the mammalian neocortex. The focus of this paper is in a systematic exploration of possibilities how to optimize important controlling parameters of the HTM model applied to the classification of hand-written digits from the USPS database. The statistical properties of this database are analyzed using the permutation test which employs a randomization distribution of the training and testing data. Based on a notion of the homogeneous usage of input image pixels, a methodology of the HTM parameter optimization is proposed. In order to study effects of two substantial parameters of the architecture: the patch size and the overlap in more details, we have restricted ourselves to the single-level HTM networks. A novel method for construction of the training sequences by ordering series of the static images is developed. A novel method for estimation of the parameter maxDist based on the box counting method is proposed. The parameter sigma of the inference Gaussian is optimized on the basis of the maximization of the belief distribution entropy. Both optimization algorithms can be equally applied to the multi-level HTM networks as well. The influences of the parameters transitionMemory and requestedGroupCount on the HTM network performance have been explored. Altogether, we have investigated 2736 different HTM network configurations. The obtained classification accuracy results have been benchmarked with the published results of several conventional classifiers.

  14. System for Oriya handwritten numeral recognition

    Science.gov (United States)

    Tripathy, N.; Panda, M.; Pal, U.

    2003-12-01

    To take care of variability involved in the writing style of different individuals, a scheme for off-line Oriya isolated handwritten numeral recognition is presented here. Oriya is a popular script in India. The scheme is mainly based on features obtained from water reservoir concept as well as topological and structural features of the numerals. Reservoir based features like number of reservoirs, their size, heights and positions, water flow direction, topological feature like number of loops, centre of gravity positions of loops, the ratio of reservoir/loop height to the numeral height, profile based features, features based on jump discontinuity etc. are some of the features used in the recognition scheme. The proposed scheme is tested on 3550 data collected from different individuals of various background and we obtained an overall recognition accuracy of about 97.74%.

  15. 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%.

  16. 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.

  17. 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.

  18. 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

  19. 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

  20. Arabic Handwritten Word Recognition Using HMMs with Explicit State Duration

    OpenAIRE

    Sellami, M.; Ennaji, A.; A. Benouareth

    2008-01-01

    We describe an offline unconstrained Arabic handwritten word recognition system based on segmentation-free approach and discrete hidden Markov models (HMMs) with explicit state duration. Character durations play a significant part in the recognition of cursive handwriting. The duration information is still mostly disregarded in HMM-based automatic cursive handwriting recognizers due to the fact that HMMs are deficient in modeling character durations properly. We will show experimentally that ...

  1. Recognition of Arabic handwritten words using contextual character models

    Science.gov (United States)

    El-Hajj, Ramy; Mokbel, Chafic; Likforman-Sulem, Laurence

    2008-01-01

    In this paper we present a system for the off-line recognition of cursive Arabic handwritten words. This system in an enhanced version of our reference system presented in [El-Hajj et al., 05] which is based on Hidden Markov Models (HMMs) and uses a sliding window approach. The enhanced version proposed here uses contextual character models. This approach is motivated by the fact that the set of Arabic characters includes a lot of ascending and descending strokes which overlap with one or two neighboring characters. Additional character models are constructed according to characters in their left or right neighborhood. Our experiments on images of the benchmark IFN/ENIT database of handwritten villages/towns names show that using contextual character models improves recognition. For a lexicon of 306 name classes, accuracy is increased by 0.6% in absolute value which corresponds to a 7.8% reduction in error rate.

  2. Classification of handwritten digits using a RAM neural net architecture

    DEFF Research Database (Denmark)

    Jørgensen, T.M.

    1997-01-01

    Results are reported on the task of recognizing handwritten digits without any advanced pre-processing. The result are obtained using a RAM-based neural network, making use of small receptive fields. Furthermore, a technique that introduces negative weights into the RAM net is reported. The results...

  3. Embedded Bernoulli Mixture HMMs for Continuous Handwritten Text Recognition

    Science.gov (United States)

    Giménez, Adrià; Juan, Alfons

    Hidden Markov Models (HMMs) are now widely used in off-line handwritten text recognition. As in speech recognition, they are usually built from shared, embedded HMMs at symbol level, in which state-conditional probability density functions are modelled with Gaussian mixtures. In contrast to speech recognition, however, it is unclear which kind of real-valued features should be used and, indeed, very different features sets are in use today. In this paper, we propose to by-pass feature extraction and directly fed columns of raw, binary image pixels into embedded Bernoulli mixture HMMs, that is, embedded HMMs in which the emission probabilities are modelled with Bernoulli mixtures. The idea is to ensure that no discriminative information is filtered out during feature extraction, which in some sense is integrated into the recognition model. Good empirical results are reported on the well-known IAM database.

  4. 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

  5. Arabic Handwritten Word Recognition Using HMMs with Explicit State Duration

    Directory of Open Access Journals (Sweden)

    M. Sellami

    2008-05-01

    Full Text Available We describe an offline unconstrained Arabic handwritten word recognition system based on segmentation-free approach and discrete hidden Markov models (HMMs with explicit state duration. Character durations play a significant part in the recognition of cursive handwriting. The duration information is still mostly disregarded in HMM-based automatic cursive handwriting recognizers due to the fact that HMMs are deficient in modeling character durations properly. We will show experimentally that explicit state duration modeling in the HMM framework can significantly improve the discriminating capacity of the HMMs to deal with very difficult pattern recognition tasks such as unconstrained Arabic handwriting recognition. In order to carry out the letter and word model training and recognition more efficiently, we propose a new version of the Viterbi algorithm taking into account explicit state duration modeling. Three distributions (Gamma, Gauss, and Poisson for the explicit state duration modeling have been used, and a comparison between them has been reported. To perform word recognition, the described system uses an original sliding window approach based on vertical projection histogram analysis of the word and extracts a new pertinent set of statistical and structural features from the word image. Several experiments have been performed using the IFN/ENIT benchmark database and the best recognition performances achieved by our system outperform those reported recently on the same database.

  6. HANDWRITTEN TEXT RECOGNITION USING A MULTIPLE­AGENT ARCHITECTURE TO ADAPT THE RECOGNITION TASK

    NARCIS (Netherlands)

    Heutte, L.; Paquet, T.; Nosary, A.; Hernoux, C.

    2004-01-01

    This communication investigates the automatic reading of unconstrained omni­writer handwritten texts. It shows how to endow the reading system with learning faculties necessary to adapt the recognition to each writer\\\\\\'s handwriting. In the first part of this communication, we explain how the

  7. IMPROVEMENT IN HANDWRITTEN NUMERAL STRING RECOGNITION BY SLANT NORMALIZATION AND CONTEXTUAL INFORMATION

    NARCIS (Netherlands)

    Britto jr., A. de S.; Sabourin, R.; Lethelier, E.; Bortolozzi, F.; Suen, C.Y.

    2004-01-01

    This work describes a way of enhancing handwritten numeral string recognition by considering slant normalization and contextual information to train an implicit segmentation­based system. A word slant normalization method is modified in order to improve the results for handwritten numeral strings.

  8. Ensemble methods for handwritten digit recognition

    DEFF Research Database (Denmark)

    Hansen, Lars Kai; Liisberg, Christian; Salamon, P.

    1992-01-01

    by optimizing the receptive fields. It is concluded that it is possible to improve performance significantly by introducing moderate-size ensembles; in particular, a 20-25% improvement has been found. The ensemble random LUTs, when trained on a medium-size database, reach a performance (without rejects) of 94....... It is further shown that it is possible to estimate the ensemble performance as well as the learning curve on a medium-size database. In addition the authors present preliminary analysis of experiments on a large database and show that state-of-the-art performance can be obtained using the ensemble approach...

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

    Directory of Open Access Journals (Sweden)

    Gaurav Y. Tawde

    2014-02-01

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

  10. 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.

  11. RESULTS FROM A PERFORMANCE EVALUATION OF HANDWRITTEN ADDRESS RECOGNITION SYSTEMS FOR THE UNITED STATES POSTAL SERVICE

    NARCIS (Netherlands)

    D'Amato, D.P.; Kuebert, E.J.; Lawson, A.

    2004-01-01

    For a cost­incentive­based procurement (known as HIP), the U.S. Postal Service (USPS) developed a methodology to predict the recognition performance of Remote Computer Reader (RCR) systems for handwritten letter mail. Very high volumes of mail in the United States mean that slight changes in mail

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

    Science.gov (United States)

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

    2010-02-01

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

  13. 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%.

  14. 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.

  15. Detection of Ambiguous Patterns Using SVMs: Application to Handwritten Numeral Recognition

    Science.gov (United States)

    Seijas, Leticia; Segura, Enrique

    This work presents a pattern recognition system that is able to detect ambiguous patterns and explain its answers. The system consists of a set of parallel Support Vector Machine (SVM) classifiers, each one dedicated to a representative feature extracted from the input, followed by an analysing module based on a bayesian strategy in charge of defining the system answer. We apply the system to the recognition of handwritten numerals. Experiments were carried out on the MNIST database, which is generally accepted as one of the standards in most of the literature in the field.

  16. Recognition of online handwritten Gurmukhi characters based on ...

    Indian Academy of Sciences (India)

    Karun Verma

    the dataset of 428 characters each written by 10 users. Keywords. Gurmukhi script; SVM; handwriting recognition; pre-processing; post-processing. 1. Introduction. Computer human interface is one of the buzzwords these days owing to the invention of touch- and pen-based input devices in PDAs, and other computing ...

  17. A novel handwritten character recognition system using gradient ...

    Indian Academy of Sciences (India)

    2School of Computer Sciences, Mahatma Gandhi University, Kottayam 686 560, India. 3Department of Computer Science, University of Kerala, Kariavattom,. Thiruvananthapuram 695 ...... Srihari S N, Yang X and Ball G R 2007 Offline Chinese handwriting recognition: An assessment of current technology. Front. Comput.

  18. Handwritten Chinese character recognition based on supervised competitive learning neural network and block-based relative fuzzy feature extraction

    Science.gov (United States)

    Sun, Limin; Wu, Shuanhu

    2005-02-01

    Offline handwritten chinese character recognition is still a difficult problem because of its large stroke changes, writing anomaly, and the difficulty for obtaining its stroke ranking information. Generally, offline handwritten chinese character can be divided into two procedures: feature extraction for capturing handwritten chinese character information and feature classifying for character recognition. In this paper, we proposed a new Chinese character recognition algorithm. In feature extraction part, we adopted elastic mesh dividing method for extracting the block features and its relative fuzzy features that utilized the relativities between different strokes and distribution probability of a stroke in its neighbor sub-blocks. In recognition part, we constructed a classifier based on a supervised competitive learning algorithm to train competitive learning neural network with the extracted features set. Experimental results show that the performance of our algorithm is encouraging and can be comparable to other algorithms.

  19. Recognition of handwritten similar Chinese characters by self-growing probabilistic decision-based neural network.

    Science.gov (United States)

    Fu, H C; Xu, Y Y; Chang, H Y

    1999-12-01

    Recognition of similar (confusion) characters is a difficult problem in optical character recognition (OCR). In this paper, we introduce a neural network solution that is capable of modeling minor differences among similar characters, and is robust to various personal handwriting styles. The Self-growing Probabilistic Decision-based Neural Network (SPDNN) is a probabilistic type neural network, which adopts a hierarchical network structure with nonlinear basis functions and a competitive credit-assignment scheme. Based on the SPDNN model, we have constructed a three-stage recognition system. First, a coarse classifier determines a character to be input to one of the pre-defined subclasses partitioned from a large character set, such as Chinese mixed with alphanumerics. Then a character recognizer determines the input image which best matches the reference character in the subclass. Lastly, the third module is a similar character recognizer, which can further enhance the recognition accuracy among similar or confusing characters. The prototype system has demonstrated a successful application of SPDNN to similar handwritten Chinese recognition for the public database CCL/HCCR1 (5401 characters x200 samples). Regarding performance, experiments on the CCL/HCCR1 database produced 90.12% recognition accuracy with no rejection, and 94.11% accuracy with 6.7% rejection, respectively. This recognition accuracy represents about 4% improvement on the previously announced performance. As to processing speed, processing before recognition (including image preprocessing, segmentation, and feature extraction) requires about one second for an A4 size character image, and recognition consumes approximately 0.27 second per character on a Pentium-100 based personal computer, without use of any hardware accelerator or co-processor.

  20. Off-Line Handwritten Signature Recognition by Wavelet Entropy and Neural Network

    Directory of Open Access Journals (Sweden)

    Khaled Daqrouq

    2017-05-01

    Full Text Available Handwritten signatures are widely utilized as a form of personal recognition. However, they have the unfortunate shortcoming of being easily abused by those who would fake the identification or intent of an individual which might be very harmful. Therefore, the need for an automatic signature recognition system is crucial. In this paper, a signature recognition approach based on a probabilistic neural network (PNN and wavelet transform average framing entropy (AFE is proposed. The system was tested with a wavelet packet (WP entropy denoted as a WP entropy neural network system (WPENN and with a discrete wavelet transform (DWT entropy denoted as a DWT entropy neural network system (DWENN. Our investigation was conducted over several wavelet families and different entropy types. Identification tasks, as well as verification tasks, were investigated for a comprehensive signature system study. Several other methods used in the literature were considered for comparison. Two databases were used for algorithm testing. The best recognition rate result was achieved by WPENN whereby the threshold entropy reached 92%.

  1. Learning Spatial-Semantic Context with Fully Convolutional Recurrent Network for Online Handwritten Chinese Text Recognition.

    Science.gov (United States)

    Xie, Zecheng; Sun, Zenghui; Jin, Lianwen; Ni, Hao; Lyons, Terry

    2017-07-28

    Online handwritten Chinese text recognition (OHCTR) is a challenging problem as it involves a large-scale character set, ambiguous segmentation, and variable-length input sequences. In this paper, we exploit the outstanding capability of path signature to translate online pen-tip trajectories into informative signature feature maps, successfully capturing the analytic and geometric properties of pen strokes with strong local invariance and robustness. A multi-spatial-context fully convolutional recurrent network (MC-FCRN) is proposed to exploit the multiple spatial contexts from the signature feature maps and generate a prediction sequence while completely avoiding the difficult segmentation problem. Furthermore, an implicit language model is developed to make predictions based on semantic context within a predicting feature sequence, providing a new perspective for incorporating lexicon constraints and prior knowledge about a certain language in the recognition procedure. Experiments on two standard benchmarks, Dataset-CASIA and Dataset-ICDAR, yielded outstanding results, with correct rates of 97.50% and 96.58%, respectively, which are significantly better than the best result reported thus far in the literature.

  2. Markov random field-based statistical character structure modeling for handwritten Chinese character recognition.

    Science.gov (United States)

    Zeng, Jia; Liu, Zhi-Qiang

    2008-05-01

    This paper proposes a statistical-structural character modeling method based on Markov random fields (MRFs) for handwritten Chinese character recognition (HCCR). The stroke relationships of a Chinese character reflect its structure, which can be statistically represented by the neighborhood system and clique potentials within the MRF framework. Based on the prior knowledge of character structures, we design the neighborhood system that accounts for the most important stroke relationships. We penalize the structurally mismatched stroke relationships with MRFs using the prior clique potentials, and derive the likelihood clique potentials from Gaussian mixture models, which encode the large variations of stroke relationships statistically. In the proposed HCCR system, we use the single-site likelihood clique potentials to extract many candidate strokes from character images, and use the pairsite clique potentials to determine the best structural match between the input candidate strokes and the MRF-based character models by relaxation labeling. The experiments on the KAIST character database demonstrate that MRFs can statistically model character structures, and work well in the HCCR system.

  3. Identifying images of handwritten digits using deep learning in H2O

    Science.gov (United States)

    Sadhasivam, Jayakumar; Charanya, R.; Kumar, S. Harish; Srinivasan, A.

    2017-11-01

    Automatic digit recognition is of popular interest today. Deep learning techniques make it possible for object recognition in image data. Perceiving the digit has turned into a fundamental part as far as certifiable applications. Since, digits are composed in various styles in this way to distinguish the digit it is important to perceive and arrange it with the assistance of machine learning methods. This exploration depends on supervised learning vector quantization neural system arranged under counterfeit artificial neural network. The pictures of digits are perceived, prepared and tried. After the system is made digits are prepared utilizing preparing dataset vectors and testing is connected to the pictures of digits which are separated to each other by fragmenting the picture and resizing the digit picture as needs be for better precision.

  4. Classification and recognition of handwritten digits by using ...

    Indian Academy of Sciences (India)

    Department of Computer Science and Engineering and Information Technology, Godavari Institute of Engineering and Technology, Rajahmundary 533 296; Department of Computer Science and Engineering and Information Technology, Rayapati Venkata Ranga Rao (RVR) and Jagarlamudi Chandramouli (JC) College of ...

  5. Deep Convolutional Extreme Learning Machine and Its Application in Handwritten Digit Classification

    Directory of Open Access Journals (Sweden)

    Shan Pang

    2016-01-01

    Full Text Available In recent years, some deep learning methods have been developed and applied to image classification applications, such as convolutional neuron network (CNN and deep belief network (DBN. However they are suffering from some problems like local minima, slow convergence rate, and intensive human intervention. In this paper, we propose a rapid learning method, namely, deep convolutional extreme learning machine (DC-ELM, which combines the power of CNN and fast training of ELM. It uses multiple alternate convolution layers and pooling layers to effectively abstract high level features from input images. Then the abstracted features are fed to an ELM classifier, which leads to better generalization performance with faster learning speed. DC-ELM also introduces stochastic pooling in the last hidden layer to reduce dimensionality of features greatly, thus saving much training time and computation resources. We systematically evaluated the performance of DC-ELM on two handwritten digit data sets: MNIST and USPS. Experimental results show that our method achieved better testing accuracy with significantly shorter training time in comparison with deep learning methods and other ELM methods.

  6. Deep Convolutional Extreme Learning Machine and Its Application in Handwritten Digit Classification.

    Science.gov (United States)

    Pang, Shan; Yang, Xinyi

    2016-01-01

    In recent years, some deep learning methods have been developed and applied to image classification applications, such as convolutional neuron network (CNN) and deep belief network (DBN). However they are suffering from some problems like local minima, slow convergence rate, and intensive human intervention. In this paper, we propose a rapid learning method, namely, deep convolutional extreme learning machine (DC-ELM), which combines the power of CNN and fast training of ELM. It uses multiple alternate convolution layers and pooling layers to effectively abstract high level features from input images. Then the abstracted features are fed to an ELM classifier, which leads to better generalization performance with faster learning speed. DC-ELM also introduces stochastic pooling in the last hidden layer to reduce dimensionality of features greatly, thus saving much training time and computation resources. We systematically evaluated the performance of DC-ELM on two handwritten digit data sets: MNIST and USPS. Experimental results show that our method achieved better testing accuracy with significantly shorter training time in comparison with deep learning methods and other ELM methods.

  7. Fast, Simple and Accurate Handwritten Digit Classification by Training Shallow Neural Network Classifiers with the 'Extreme Learning Machine' Algorithm.

    Directory of Open Access Journals (Sweden)

    Mark D McDonnell

    Full Text Available Recent advances in training deep (multi-layer architectures have inspired a renaissance in neural network use. For example, deep convolutional networks are becoming the default option for difficult tasks on large datasets, such as image and speech recognition. However, here we show that error rates below 1% on the MNIST handwritten digit benchmark can be replicated with shallow non-convolutional neural networks. This is achieved by training such networks using the 'Extreme Learning Machine' (ELM approach, which also enables a very rapid training time (∼ 10 minutes. Adding distortions, as is common practise for MNIST, reduces error rates even further. Our methods are also shown to be capable of achieving less than 5.5% error rates on the NORB image database. To achieve these results, we introduce several enhancements to the standard ELM algorithm, which individually and in combination can significantly improve performance. The main innovation is to ensure each hidden-unit operates only on a randomly sized and positioned patch of each image. This form of random 'receptive field' sampling of the input ensures the input weight matrix is sparse, with about 90% of weights equal to zero. Furthermore, combining our methods with a small number of iterations of a single-batch backpropagation method can significantly reduce the number of hidden-units required to achieve a particular performance. Our close to state-of-the-art results for MNIST and NORB suggest that the ease of use and accuracy of the ELM algorithm for designing a single-hidden-layer neural network classifier should cause it to be given greater consideration either as a standalone method for simpler problems, or as the final classification stage in deep neural networks applied to more difficult problems.

  8. Fast, Simple and Accurate Handwritten Digit Classification by Training Shallow Neural Network Classifiers with the 'Extreme Learning Machine' Algorithm.

    Science.gov (United States)

    McDonnell, Mark D; Tissera, Migel D; Vladusich, Tony; van Schaik, André; Tapson, Jonathan

    2015-01-01

    Recent advances in training deep (multi-layer) architectures have inspired a renaissance in neural network use. For example, deep convolutional networks are becoming the default option for difficult tasks on large datasets, such as image and speech recognition. However, here we show that error rates below 1% on the MNIST handwritten digit benchmark can be replicated with shallow non-convolutional neural networks. This is achieved by training such networks using the 'Extreme Learning Machine' (ELM) approach, which also enables a very rapid training time (∼ 10 minutes). Adding distortions, as is common practise for MNIST, reduces error rates even further. Our methods are also shown to be capable of achieving less than 5.5% error rates on the NORB image database. To achieve these results, we introduce several enhancements to the standard ELM algorithm, which individually and in combination can significantly improve performance. The main innovation is to ensure each hidden-unit operates only on a randomly sized and positioned patch of each image. This form of random 'receptive field' sampling of the input ensures the input weight matrix is sparse, with about 90% of weights equal to zero. Furthermore, combining our methods with a small number of iterations of a single-batch backpropagation method can significantly reduce the number of hidden-units required to achieve a particular performance. Our close to state-of-the-art results for MNIST and NORB suggest that the ease of use and accuracy of the ELM algorithm for designing a single-hidden-layer neural network classifier should cause it to be given greater consideration either as a standalone method for simpler problems, or as the final classification stage in deep neural networks applied to more difficult problems.

  9. A Simple Shallow Convolutional Neural Network for Accurate Handwritten Digit Classification

    OpenAIRE

    Golovko, V.; Mikhno, E.; Brichk, A.

    2016-01-01

    At present the deep neural network is the hottest topic in the domain of machine learning and can accomplish a deep hierarchical representation of the input data. Due to deep architecture the large convolutional neural networks can reach very small test error rates below 0.4% using the MNIST database. In this work we have shown, that high accuracy can be achieved using reduced shallow convolutional neural network without adding distortions for digits. The main contribu...

  10. Connected digit speech recognition system for Malayalam

    Indian Academy of Sciences (India)

    A connected digit speech recognition is important in many applications such as automated banking system, catalogue-dialing, automatic data entry, automated banking system, etc. This paper presents an optimum speaker-independent connected digit recognizer for Malayalam language. The system employs Perceptual ...

  11. A Novel Two-Stage Spectrum-Based Approach for Dimensionality Reduction: A Case Study on the Recognition of Handwritten Numerals

    Directory of Open Access Journals (Sweden)

    Mohammad Amin Shayegan

    2014-01-01

    Full Text Available Dimensionality reduction (feature selection is an important step in pattern recognition systems. Although there are different conventional approaches for feature selection, such as Principal Component Analysis, Random Projection, and Linear Discriminant Analysis, selecting optimal, effective, and robust features is usually a difficult task. In this paper, a new two-stage approach for dimensionality reduction is proposed. This method is based on one-dimensional and two-dimensional spectrum diagrams of standard deviation and minimum to maximum distributions for initial feature vector elements. The proposed algorithm is validated in an OCR application, by using two big standard benchmark handwritten OCR datasets, MNIST and Hoda. In the beginning, a 133-element feature vector was selected from the most used features, proposed in the literature. Finally, the size of initial feature vector was reduced from 100% to 59.40% (79 elements for the MNIST dataset, and to 43.61% (58 elements for the Hoda dataset, in order. Meanwhile, the accuracies of OCR systems are enhanced 2.95% for the MNIST dataset, and 4.71% for the Hoda dataset. The achieved results show an improvement in the precision of the system in comparison to the rival approaches, Principal Component Analysis and Random Projection. The proposed technique can also be useful for generating decision rules in a pattern recognition system using rule-based classifiers.

  12. Automatic forensic face recognition from digital images.

    Science.gov (United States)

    Peacock, C; Goode, A; Brett, A

    2004-01-01

    Digital image evidence is now widely available from criminal investigations and surveillance operations, often captured by security and surveillance CCTV. This has resulted in a growing demand from law enforcement agencies for automatic person-recognition based on image data. In forensic science, a fundamental requirement for such automatic face recognition is to evaluate the weight that can justifiably be attached to this recognition evidence in a scientific framework. This paper describes a pilot study carried out by the Forensic Science Service (UK) which explores the use of digital facial images in forensic investigation. For the purpose of the experiment a specific software package was chosen (Image Metrics Optasia). The paper does not describe the techniques used by the software to reach its decision of probabilistic matches to facial images, but accepts the output of the software as though it were a 'black box'. In this way, the paper lays a foundation for how face recognition systems can be compared in a forensic framework. The aim of the paper is to explore how reliably and under what conditions digital facial images can be presented in evidence.

  13. Transcription of Spanish Historical Handwritten Documents with Deep Neural Networks

    Directory of Open Access Journals (Sweden)

    Emilio Granell

    2018-01-01

    Full Text Available The digitization of historical handwritten document images is important for the preservation of cultural heritage. Moreover, the transcription of text images obtained from digitization is necessary to provide efficient information access to the content of these documents. Handwritten Text Recognition (HTR has become an important research topic in the areas of image and computational language processing that allows us to obtain transcriptions from text images. State-of-the-art HTR systems are, however, far from perfect. One difficulty is that they have to cope with image noise and handwriting variability. Another difficulty is the presence of a large amount of Out-Of-Vocabulary (OOV words in ancient historical texts. A solution to this problem is to use external lexical resources, but such resources might be scarce or unavailable given the nature and the age of such documents. This work proposes a solution to avoid this limitation. It consists of associating a powerful optical recognition system that will cope with image noise and variability, with a language model based on sub-lexical units that will model OOV words. Such a language modeling approach reduces the size of the lexicon while increasing the lexicon coverage. Experiments are first conducted on the publicly available Rodrigo dataset, which contains the digitization of an ancient Spanish manuscript, with a recognizer based on Hidden Markov Models (HMMs. They show that sub-lexical units outperform word units in terms of Word Error Rate (WER, Character Error Rate (CER and OOV word accuracy rate. This approach is then applied to deep net classifiers, namely Bi-directional Long-Short Term Memory (BLSTMs and Convolutional Recurrent Neural Nets (CRNNs. Results show that CRNNs outperform HMMs and BLSTMs, reaching the lowest WER and CER for this image dataset and significantly improving OOV recognition.

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

    Science.gov (United States)

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

    2017-06-01

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

  15. 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.

  16. Enhancing spoken connected-digit recognition accuracy by error ...

    Indian Academy of Sciences (India)

    Recognizing spoken connected-digit numbers accurately is an important problem and has very many applications. Though state-of-the-art word recognition systems have gained acceptable accuracy levels, the accuracy of recognition of current connected spoken digits (and other short words) is very poor. In this paper, we ...

  17. Symbol detection in online handwritten graphics using Faster R-CNN

    OpenAIRE

    Julca-Aguilar, Frank D.; Hirata, Nina S. T.

    2017-01-01

    Symbol detection techniques in online handwritten graphics (e.g. diagrams and mathematical expressions) consist of methods specifically designed for a single graphic type. In this work, we evaluate the Faster R-CNN object detection algorithm as a general method for detection of symbols in handwritten graphics. We evaluate different configurations of the Faster R-CNN method, and point out issues relative to the handwritten nature of the data. Considering the online recognition context, we eval...

  18. Digital signal processing algorithms for automatic voice recognition

    Science.gov (United States)

    Botros, Nazeih M.

    1987-11-01

    The current digital signal analysis algorithms are investigated that are implemented in automatic voice recognition algorithms. Automatic voice recognition means, the capability of a computer to recognize and interact with verbal commands. The digital signal is focused on, rather than the linguistic, analysis of speech signal. Several digital signal processing algorithms are available for voice recognition. Some of these algorithms are: Linear Predictive Coding (LPC), Short-time Fourier Analysis, and Cepstrum Analysis. Among these algorithms, the LPC is the most widely used. This algorithm has short execution time and do not require large memory storage. However, it has several limitations due to the assumptions used to develop it. The other 2 algorithms are frequency domain algorithms with not many assumptions, but they are not widely implemented or investigated. However, with the recent advances in the digital technology, namely signal processors, these 2 frequency domain algorithms may be investigated in order to implement them in voice recognition. This research is concerned with real time, microprocessor based recognition algorithms.

  19. Digital signal processing algorithms for automatic voice recognition

    Science.gov (United States)

    Botros, Nazeih M.

    1987-01-01

    The current digital signal analysis algorithms are investigated that are implemented in automatic voice recognition algorithms. Automatic voice recognition means, the capability of a computer to recognize and interact with verbal commands. The digital signal is focused on, rather than the linguistic, analysis of speech signal. Several digital signal processing algorithms are available for voice recognition. Some of these algorithms are: Linear Predictive Coding (LPC), Short-time Fourier Analysis, and Cepstrum Analysis. Among these algorithms, the LPC is the most widely used. This algorithm has short execution time and do not require large memory storage. However, it has several limitations due to the assumptions used to develop it. The other 2 algorithms are frequency domain algorithms with not many assumptions, but they are not widely implemented or investigated. However, with the recent advances in the digital technology, namely signal processors, these 2 frequency domain algorithms may be investigated in order to implement them in voice recognition. This research is concerned with real time, microprocessor based recognition algorithms.

  20. 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

  1. Beyond OCR : Multi-faceted understanding of handwritten document characteristics

    NARCIS (Netherlands)

    He, Sheng; Schomaker, Lambert

    Handwritten document understanding is a fundamental research problem in pattern recognition and it relies on the effective features. In this paper, we propose a joint feature distribution (JFD) principle to design novel discriminative features which could be the joint distribution of features on

  2. Handwritten-word spotting using biologically inspired features

    NARCIS (Netherlands)

    van der Zant, Tijn; Schomaker, Lambert; Haak, Koen

    2008-01-01

    For quick access to new handwritten collections, current handwriting recognition methods are too cumbersome. They cannot deal with the lack of labeled data and would require extensive laboratory training for each individual script, style, language, and collection. We propose a biologically inspired

  3. Investigation of efficient features for image recognition by neural networks.

    Science.gov (United States)

    Goltsev, Alexander; Gritsenko, Vladimir

    2012-04-01

    In the paper, effective and simple features for image recognition (named LiRA-features) are investigated in the task of handwritten digit recognition. Two neural network classifiers are considered-a modified 3-layer perceptron LiRA and a modular assembly neural network. A method of feature selection is proposed that analyses connection weights formed in the preliminary learning process of a neural network classifier. In the experiments using the MNIST database of handwritten digits, the feature selection procedure allows reduction of feature number (from 60 000 to 7000) preserving comparable recognition capability while accelerating computations. Experimental comparison between the LiRA perceptron and the modular assembly neural network is accomplished, which shows that recognition capability of the modular assembly neural network is somewhat better. Copyright © 2011 Elsevier Ltd. All rights reserved.

  4. A Proposed Arabic Handwritten Text Normalization Method

    Directory of Open Access Journals (Sweden)

    Tarik Abu-Ain

    2014-11-01

    Full Text Available Text normalization is an important technique in document image analysis and recognition. It consists of many preprocessing stages, which include slope correction, text padding, skew correction, and straight the writing line. In this side, text normalization has an important role in many procedures such as text segmentation, feature extraction and characters recognition. In the present article, a new method for text baseline detection, straightening, and slant correction for Arabic handwritten texts is proposed. The method comprises a set of sequential steps: first components segmentation is done followed by components text thinning; then, the direction features of the skeletons are extracted, and the candidate baseline regions are determined. After that, selection of the correct baseline region is done, and finally, the baselines of all components are aligned with the writing line.  The experiments are conducted on IFN/ENIT benchmark Arabic dataset. The results show that the proposed method has a promising and encouraging performance.

  5. Leave-one-out-training and leave-one-out-testing hidden markov models for a handwritten numeral recognizer: the implications of a single classifier and multiple classifications.

    Science.gov (United States)

    Ko, Albert Hung-Ren; Cavalin, Paulo Rodrigo; Sabourin, Robert; de Souza Britto, Alceu

    2009-12-01

    Hidden Markov Models (HMMs) have been shown to be useful in handwritten pattern recognition. However, owing to their fundamental structure, they have little resistance to unexpected noise among observation sequences. In other words, unexpected noise in a sequence might "break" the normal transmission of states for this sequence, making it unrecognizable to trained models. To resolve this problem, we propose a leave-one-out-training strategy, which will make the models more robust. We also propose a leave-one-out-testing method, which will compensate for some of the negative effects of this noise. The latter is actually an example of a system with a single classifier and multiple classifications. Compared with the 98.00 percent accuracy of the benchmark HMMs, the new system achieves a 98.88 percent accuracy rate on handwritten digits.

  6. Feature-Based Digital Modulation Recognition Using Compressive Sampling

    Directory of Open Access Journals (Sweden)

    Zhuo Sun

    2016-01-01

    Full Text Available Compressive sensing theory can be applied to reconstruct the signal with far fewer measurements than what is usually considered necessary, while in many scenarios, such as spectrum detection and modulation recognition, we only expect to acquire useful characteristics rather than the original signals, where selecting the feature with sparsity becomes the main challenge. With the aim of digital modulation recognition, the paper mainly constructs two features which can be recovered directly from compressive samples. The two features are the spectrum of received data and its nonlinear transformation and the compositional feature of multiple high-order moments of the received data; both of them have desired sparsity required for reconstruction from subsamples. Recognition of multiple frequency shift keying, multiple phase shift keying, and multiple quadrature amplitude modulation are considered in our paper and implemented in a unified procedure. Simulation shows that the two identification features can work effectively in the digital modulation recognition, even at a relatively low signal-to-noise ratio.

  7. Automatic out-of-range photo recognition using digital techniques

    Science.gov (United States)

    Dardier, Genevieve; Maitre, Henri

    1998-09-01

    This paper addresses digital techniques used to identify automatically those color photographs whose optical densities fall outside acceptable norms for a visual system. Targets are of two different kinds indicating the need for different recognition algorithms. First, the investigation focuses on color pictures showing high contrast in optical densities such as pictures taken with flash and pictures taken against the light; it estimates statistical parameters which determine mixture densities. Results of Maximum Likelihood, Moment estimation using Prony's Method, Multiscale Analysis and Marquardt optimization algorithm applied to the histogram recognition problem have been compared in terms of efficiency and speed for both low and more detailed vision. Attention is then focussed on pictures showing an optical density gradient in a given direction. Solutions such as plane fitting, robust Median Based Estimator are compared with a new '4-step Median Based Estimator.'

  8. An Information Extraction model for unconstrained handwritten documents

    OpenAIRE

    Thomas, Simon; Chatelain, Clement; Heutte, Laurent; Paquet, Thierry

    2010-01-01

    International audience; In this paper, a new information extraction system by statistical shallow parsing in unconstrained handwritten documents is introduced. Unlike classical approaches found in the literature as keyword spotting or full document recognition, our approch relies on a strong and powerful global handwriting model. A entire text line is considered as an indivisible entity and is modeled with Hidden Markov Models. In this way, text line shallow parsing allows fast extraction of ...

  9. Extended Method of Digital Modulation Recognition and Its Testing

    Directory of Open Access Journals (Sweden)

    A. Kubankova

    2011-04-01

    Full Text Available The paper describes a new method for the classification of digital modulations. ASK, 2FSK, 4FSK, MSK, BPSK, QPSK, 8PSK and 16QAM were chosen for recognition as best known digital modulations used in modern communication technologies. The maximum value of the spectral power density of the normalized-centered instantaneous amplitude of the received signal is used to discriminate between frequency modulations (2FSK, 4FSK and MSK on one hand and amplitude and phase modulations (ASK, BPSK, QPSK, 8PSK and 16QAM on the other hand. Then the 2FSK, 4FSK and MSK modulations are classified by means of spectrums. The histograms of the instantaneous phase are used to discriminate between ASK, BPSK, QPSK, 8PSK and 16QAM. The method designed was tested with simulated and measured signals corrupted by white Gaussian noise.

  10. Word segmentation of off-line handwritten documents

    Science.gov (United States)

    Huang, Chen; Srihari, Sargur N.

    2008-01-01

    Word segmentation is the most critical pre-processing step for any handwritten document recognition and/or retrieval system. When the writing style is unconstrained (written in a natural manner), recognition of individual components may be unreliable, so they must be grouped together into word hypotheses before recognition algorithms can be used. This paper describes a gap metrics based machine learning approach to separate a line of unconstrained handwritten text into words. Our approach uses a set of both local and global features, which is motivated by the ways in which human beings perform this kind of task. In addition, in order to overcome the disadvantage of different distance computation methods, we propose a combined distance measure computed using three different methods. The classification is done by using a three-layer neural network. The algorithm is evaluated using an unconstrained handwriting database that contains 50 pages (1026 line, 7562 words images) handwritten documents. The overall accuracy is 90.8%, which shows a better performance than a previous method.

  11. First experiments on a new online handwritten flowchart database

    Science.gov (United States)

    Awal, Ahmad-Montaser; Feng, Guihuan; Mouchère, Harold; Viard-Gaudin, Christian

    2011-01-01

    We propose in this paper a new online handwritten flowchart database and perform some first experiments to have a baseline benchmark on this dataset. The collected database consists of 419 flowcharts labeled at the stroke and symbol levels. In addition, an isolated database of graphical and text symbols was extracted from these collected flowcharts. Then, we tackle the problem of online handwritten flowchart recognition from two different points of view. Firstly, we consider that flowcharts are correctly segmented, and we propose different classifiers to perform two tasks, text/non-text separation and graphical symbol recognition. Tested with the extracted isolated test database, we achieve up to 90% and 98% in text/non-text separation and up to 93.5% in graphical symbols recognition. Secondly, we propose a global approach to perform flowchart segmentation and recognition. For this latter, we adopt a global learning schema and a recognition architecture that considers a simultaneous segmentation and recognition. Global architecture is trained and tested directly with flowcharts. Results show the interest of such global approach, but regarding the complexity of flowchart segmentation problem, there is still lot of space to improve the global learning and recognition methods.

  12. Using Amazon Mechanical Turk to Transcribe Historical Handwritten Documents

    Directory of Open Access Journals (Sweden)

    Andrew S.I.D. Lang

    2011-10-01

    Full Text Available The developing “information age” is continually unraveling new ways of discovering, presenting and sharing information. Most new academic material is digitally formatted upon its creation and is thus easy to find and query. However, there remains a good deal of material from times prior to the “information age” that has yet to be converted to digital form. Much of this material can be found in library collections—whether academic, public or private—and thus remains available only to a limited number of locals or willing-and-able sojourners. Using OCR technology, most typeset documents can be digitized and made available online; and there are several projects underway to do exactly this. However, there remains little to be done for handwritten materials. Those who own collections of handwritten documents are increasingly wanting to make the content thereof available to the general public. Unfortunately, traditional transcription models typically prove to be expensive or inefficient and pdf snapshots are not searchable. We have developed a model for digital transcription using Google Docs and Amazon's Mechanical Turk. Using this model, one can use an online workforce to efficiently transcribe handwritten texts and perform quality control at a cost much lower than professional transcription services. To illustrate the model we used Amazon’s Mechanical Turk to transcribe and then proofread the Frederick Douglass Diary which we have made available on a public searchable wiki. The total cost of transcription and proofreading for the 72 page diary was less than $25.00 with some pages being transcribed and proofread for as little as $0.04. Our results show that using Amazon’s Mechanical Turk holds great promise for providing an affordable transcription method for hand-written historical documents making them easily sharable and fully searchable.

  13. Iterative cross section sequence graph for handwritten character segmentation.

    Science.gov (United States)

    Dawoud, Amer

    2007-08-01

    The iterative cross section sequence graph (ICSSG) is an algorithm for handwritten character segmentation. It expands the cross section sequence graph concept by applying it iteratively at equally spaced thresholds. The iterative thresholding reduces the effect of information loss associated with image binarization. ICSSG preserves the characters' skeletal structure by preventing the interference of pixels that causes flooding of adjacent characters' segments. Improving the structural quality of the characters' skeleton facilitates better feature extraction and classification, which improves the overall performance of optical character recognition (OCR). Experimental results showed significant improvements in OCR recognition rates compared to other well-established segmentation algorithms.

  14. Robust Digital Speech Watermarking For Online Speaker Recognition

    Directory of Open Access Journals (Sweden)

    Mohammad Ali Nematollahi

    2015-01-01

    Full Text Available A robust and blind digital speech watermarking technique has been proposed for online speaker recognition systems based on Discrete Wavelet Packet Transform (DWPT and multiplication to embed the watermark in the amplitudes of the wavelet’s subbands. In order to minimize the degradation effect of the watermark, these subbands are selected where less speaker-specific information was available (500 Hz–3500 Hz and 6000 Hz–7000 Hz. Experimental results on Texas Instruments Massachusetts Institute of Technology (TIMIT, Massachusetts Institute of Technology (MIT, and Mobile Biometry (MOBIO show that the degradation for speaker verification and identification is 1.16% and 2.52%, respectively. Furthermore, the proposed watermark technique can provide enough robustness against different signal processing attacks.

  15. Comparative wavelet, PLP, and LPC speech recognition techniques on the Hindi speech digits database

    Science.gov (United States)

    Mishra, A. N.; Shrotriya, M. C.; Sharan, S. N.

    2010-02-01

    In view of the growing use of automatic speech recognition in the modern society, we study various alternative representations of the speech signal that have the potential to contribute to the improvement of the recognition performance. In this paper wavelet based features using different wavelets are used for Hindi digits recognition. The recognition performance of these features has been compared with Linear Prediction Coefficients (LPC) and Perceptual Linear Prediction (PLP) features. All features have been tested using Hidden Markov Model (HMM) based classifier for speaker independent Hindi digits recognition. The recognition performance of PLP features is11.3% better than LPC features. The recognition performance with db10 features has shown a further improvement of 12.55% over PLP features. The recognition performance with db10 is best among all wavelet based features.

  16. Neural Ctrl-F : Segmentation-free query-by-string word spotting in handwritten manuscript collections

    OpenAIRE

    Wilkinson, Tomas; Lindström, Jonas; Brun, Anders

    2017-01-01

    In this paper, we approach the problem of segmentation-free query-by-string word spotting for handwritten documents. In other words, we use methods inspired from computer vision and machine learning to search for words in large collections of digitized manuscripts. In particular, we are interested in historical handwritten texts, which are often far more challenging than modern printed documents. This task is important, as it provides people with a way to quickly find what they are looking fo...

  17. Neural Ctrl-F: Segmentation-free Query-by-String Word Spotting in Handwritten Manuscript Collections

    OpenAIRE

    Wilkinson, Tomas; Lindström, Jonas; Brun, Anders

    2017-01-01

    In this paper, we approach the problem of segmentation-free query-by-string word spotting for handwritten documents. In other words, we use methods inspired from computer vision and machine learning to search for words in large collections of digitized manuscripts. In particular, we are interested in historical handwritten texts, which are often far more challenging than modern printed documents. This task is important, as it provides people with a way to quickly find what they are looking fo...

  18. Automatic Mexican sign language and digits recognition using normalized central moments

    Science.gov (United States)

    Solís, Francisco; Martínez, David; Espinosa, Oscar; Toxqui, Carina

    2016-09-01

    This work presents a framework for automatic Mexican sign language and digits recognition based on computer vision system using normalized central moments and artificial neural networks. Images are captured by digital IP camera, four LED reflectors and a green background in order to reduce computational costs and prevent the use of special gloves. 42 normalized central moments are computed per frame and used in a Multi-Layer Perceptron to recognize each database. Four versions per sign and digit were used in training phase. 93% and 95% of recognition rates were achieved for Mexican sign language and digits respectively.

  19. Deformation models for image recognition.

    Science.gov (United States)

    Keysers, Daniel; Deselaers, Thomas; Gollan, Christian; Ney, Hermann

    2007-08-01

    We present the application of different nonlinear image deformation models to the task of image recognition. The deformation models are especially suited for local changes as they often occur in the presence of image object variability. We show that, among the discussed models, there is one approach that combines simplicity of implementation, low-computational complexity, and highly competitive performance across various real-world image recognition tasks. We show experimentally that the model performs very well for four different handwritten digit recognition tasks and for the classification of medical images, thus showing high generalization capacity. In particular, an error rate of 0.54 percent on the MNIST benchmark is achieved, as well as the lowest reported error rate, specifically 12.6 percent, in the 2005 international ImageCLEF evaluation of medical image categorization.

  20. AUTOMATIC RECOGNITION OF BOTH INTER AND INTRA CLASSES OF DIGITAL MODULATED SIGNALS USING ARTIFICIAL NEURAL NETWORK

    Directory of Open Access Journals (Sweden)

    JIDE JULIUS POPOOLA

    2014-04-01

    Full Text Available In radio communication systems, signal modulation format recognition is a significant characteristic used in radio signal monitoring and identification. Over the past few decades, modulation formats have become increasingly complex, which has led to the problem of how to accurately and promptly recognize a modulation format. In addressing these challenges, the development of automatic modulation recognition systems that can classify a radio signal’s modulation format has received worldwide attention. Decision-theoretic methods and pattern recognition solutions are the two typical automatic modulation recognition approaches. While decision-theoretic approaches use probabilistic or likelihood functions, pattern recognition uses feature-based methods. This study applies the pattern recognition approach based on statistical parameters, using an artificial neural network to classify five different digital modulation formats. The paper deals with automatic recognition of both inter-and intra-classes of digitally modulated signals in contrast to most of the existing algorithms in literature that deal with either inter-class or intra-class modulation format recognition. The results of this study show that accurate and prompt modulation recognition is possible beyond the lower bound of 5 dB commonly acclaimed in literature. The other significant contribution of this paper is the usage of the Python programming language which reduces computational complexity that characterizes other automatic modulation recognition classifiers developed using the conventional MATLAB neural network toolbox.

  1. Enhancing spoken connected-digit recognition accuracy by error ...

    Indian Academy of Sciences (India)

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

    Speech as a medium is being increasingly used in human computer interface applica- tions. There has been fair success in terms of achieving accuracy in word-based speech recognition systems and this has led to speech recognition and speaker verification systems being deployed in practical applications such as ...

  2. Implementation of age and gender recognition system for intelligent digital signage

    Science.gov (United States)

    Lee, Sang-Heon; Sohn, Myoung-Kyu; Kim, Hyunduk

    2015-12-01

    Intelligent digital signage systems transmit customized advertising and information by analyzing users and customers, unlike existing system that presented advertising in the form of broadcast without regard to type of customers. Currently, development of intelligent digital signage system has been pushed forward vigorously. In this study, we designed a system capable of analyzing gender and age of customers based on image obtained from camera, although there are many different methods for analyzing customers. We conducted age and gender recognition experiments using public database. The age/gender recognition experiments were performed through histogram matching method by extracting Local binary patterns (LBP) features after facial area on input image was normalized. The results of experiment showed that gender recognition rate was as high as approximately 97% on average. Age recognition was conducted based on categorization into 5 age classes. Age recognition rates for women and men were about 67% and 68%, respectively when that conducted separately for different gender.

  3. Recognition and inference of crevice processing on digitized paintings

    Science.gov (United States)

    Karuppiah, S. P.; Srivatsa, S. K.

    2013-03-01

    This paper is designed to detect and removal of cracks on digitized paintings. The cracks are detected by threshold. Afterwards, the thin dark brush strokes which have been misidentified as cracks are removed using Median radial basis function neural network on hue and saturation data, Semi-automatic procedure based on region growing. Finally, crack is filled using wiener filter. The paper is well designed in such a way that most of the cracks on digitized paintings have identified and removed. The paper % of betterment is 90%. This paper helps us to perform not only on digitized paintings but also the medical images and bmp images. This paper is implemented by Mat Lab.

  4. Content-based image recognition for digital radiographs

    Science.gov (United States)

    Luo, Hui; Luo, Jiebo

    2008-03-01

    Before a radiographic image is sent to a picture archiving and communications system (PACS), its projection information needs to be correctly identified at capture modalities to facilitate image archive and retrieval. Currently, annotating radiographic images is manually performed by technologists. It is labor intensive and cost ineffective. Moreover, man-made annotation errors occur frequently during image acquisition. To address this issue, an automatic image recognition method is developed. It first extracts a set of visual features from the most indicative region in a radiograph for image recognition, and then uses a family of classifiers, each of which is trained for a specific projection to determine the most appropriate projection for the image. The method has been tested on a large number of clinical images and has shown excellent robustness and efficiency.

  5. Separability versus Prototypicality in Handwritten Word Retrieval

    NARCIS (Netherlands)

    van Oosten, Jean-Paul; Schomaker, Lambertus

    User appreciation of a word-image retrieval system is based on the quality of a hit list for a query. Using support vector machines for ranking in large scale, handwritten document collections, we observed that many hit lists suffered from bad instances in the top ranks. An analysis of this problem

  6. Recognition of digital characteristics based new improved genetic algorithm

    Science.gov (United States)

    Wang, Meng; Xu, Guoqiang; Lin, Zihao

    2017-08-01

    In the field of digital signal processing, Estimating the characteristics of signal modulation parameters is an significant research direction. The paper determines the set of eigenvalue which can show the difference of the digital signal modulation based on the deep research of the new improved genetic algorithm. Firstly take them as the best gene pool; secondly, The best gene pool will be changed in the genetic evolvement by selecting, overlapping and eliminating each other; Finally, Adapting the strategy of futher enhance competition and punishment to more optimizer the gene pool and ensure each generation are of high quality gene. The simulation results show that this method not only has the global convergence, stability and faster convergence speed.

  7. Boosting bonsai trees for handwritten/printed text discrimination

    Science.gov (United States)

    Ricquebourg, Yann; Raymond, Christian; Poirriez, Baptiste; Lemaitre, Aurélie; Coüasnon, Bertrand

    2013-12-01

    Boosting over decision-stumps proved its efficiency in Natural Language Processing essentially with symbolic features, and its good properties (fast, few and not critical parameters, not sensitive to over-fitting) could be of great interest in the numeric world of pixel images. In this article we investigated the use of boosting over small decision trees, in image classification processing, for the discrimination of handwritten/printed text. Then, we conducted experiments to compare it to usual SVM-based classification revealing convincing results with very close performance, but with faster predictions and behaving far less as a black-box. Those promising results tend to make use of this classifier in more complex recognition tasks like multiclass problems.

  8. Quantify spatial relations to discover handwritten graphical symbols

    Science.gov (United States)

    Li, Jinpeng; Mouchère, Harold; Viard-Gaudin, Christian

    2012-01-01

    To model a handwritten graphical language, spatial relations describe how the strokes are positioned in the 2-dimensional space. Most of existing handwriting recognition systems make use of some predefined spatial relations. However, considering a complex graphical language, it is hard to express manually all the spatial relations. Another possibility would be to use a clustering technique to discover the spatial relations. In this paper, we discuss how to create a relational graph between strokes (nodes) labeled with graphemes in a graphical language. Then we vectorize spatial relations (edges) for clustering and quantization. As the targeted application, we extract the repetitive sub-graphs (graphical symbols) composed of graphemes and learned spatial relations. On two handwriting databases, a simple mathematical expression database and a complex flowchart database, the unsupervised spatial relations outperform the predefined spatial relations. In addition, we visualize the frequent patterns on two text-lines containing Chinese characters.

  9. Object detection and recognition in digital images theory and practice

    CERN Document Server

    Cyganek, Boguslaw

    2013-01-01

    Object detection, tracking and recognition in images are key problems in computer vision. This book provides the reader with a balanced treatment between the theory and practice of selected methods in these areas to make the book accessible to a range of researchers, engineers, developers and postgraduate students working in computer vision and related fields. Key features: Explains the main theoretical ideas behind each method (which are augmented with a rigorous mathematical derivation of the formulas), their implementation (in C++) and demonstrated working in real applications.

  10. ASM Based Synthesis of Handwritten Arabic Text Pages.

    Science.gov (United States)

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

    2015-01-01

    Document analysis tasks, as text recognition, word spotting, or segmentation, are highly dependent on comprehensive and suitable databases for training and validation. However their generation is expensive in sense of labor and time. As a matter of fact, there is a lack of such databases, which complicates research and development. This is especially true for the case of Arabic handwriting recognition, that involves different preprocessing, segmentation, and recognition methods, which have individual demands on samples and ground truth. To bypass this problem, we present an efficient system that automatically turns Arabic Unicode text into synthetic images of handwritten documents and detailed ground truth. Active Shape Models (ASMs) based on 28046 online samples were used for character synthesis and statistical properties were extracted from the IESK-arDB database to simulate baselines and word slant or skew. In the synthesis step ASM based representations are composed to words and text pages, smoothed by B-Spline interpolation and rendered considering writing speed and pen characteristics. Finally, we use the synthetic data to validate a segmentation method. An experimental comparison with the IESK-arDB database encourages to train and test document analysis related methods on synthetic samples, whenever no sufficient natural ground truthed data is available.

  11. Handwritten-word spotting using biologically inspired features.

    Science.gov (United States)

    van der Zant, Tijn; Schomaker, Lambert; Haak, Koen

    2008-11-01

    For quick access to new handwritten collections, current handwriting recognition methods are too cumbersome. They cannot deal with the lack of labeled data and would require extensive laboratory training for each individual script, style, language and collection. We propose a biologically inspired whole-word recognition method which is used to incrementally elicit word labels in a live, web-based annotation system, named Monk. Since human labor should be minimized given the massive amount of image data, it becomes important to rely on robust perceptual mechanisms in the machine. Recent computational models of the neuro-physiology of vision are applied to isolated word classification. A primate cortex-like mechanism allows to classify text-images that have a low frequency of occurrence. Typically these images are the most difficult to retrieve and often contain named entities and are regarded as the most important to people. Usually standard pattern-recognition technology cannot deal with these text-images if there are not enough labeled instances. The results of this retrieval system are compared to normalized word-image matching and appear to be very promising.

  12. ASM Based Synthesis of Handwritten Arabic Text Pages

    Directory of Open Access Journals (Sweden)

    Laslo Dinges

    2015-01-01

    Full Text Available Document analysis tasks, as text recognition, word spotting, or segmentation, are highly dependent on comprehensive and suitable databases for training and validation. However their generation is expensive in sense of labor and time. As a matter of fact, there is a lack of such databases, which complicates research and development. This is especially true for the case of Arabic handwriting recognition, that involves different preprocessing, segmentation, and recognition methods, which have individual demands on samples and ground truth. To bypass this problem, we present an efficient system that automatically turns Arabic Unicode text into synthetic images of handwritten documents and detailed ground truth. Active Shape Models (ASMs based on 28046 online samples were used for character synthesis and statistical properties were extracted from the IESK-arDB database to simulate baselines and word slant or skew. In the synthesis step ASM based representations are composed to words and text pages, smoothed by B-Spline interpolation and rendered considering writing speed and pen characteristics. Finally, we use the synthetic data to validate a segmentation method. An experimental comparison with the IESK-arDB database encourages to train and test document analysis related methods on synthetic samples, whenever no sufficient natural ground truthed data is available.

  13. ASM Based Synthesis of Handwritten Arabic Text Pages

    Science.gov (United States)

    Al-Hamadi, Ayoub; Elzobi, Moftah; El-etriby, Sherif; Ghoneim, Ahmed

    2015-01-01

    Document analysis tasks, as text recognition, word spotting, or segmentation, are highly dependent on comprehensive and suitable databases for training and validation. However their generation is expensive in sense of labor and time. As a matter of fact, there is a lack of such databases, which complicates research and development. This is especially true for the case of Arabic handwriting recognition, that involves different preprocessing, segmentation, and recognition methods, which have individual demands on samples and ground truth. To bypass this problem, we present an efficient system that automatically turns Arabic Unicode text into synthetic images of handwritten documents and detailed ground truth. Active Shape Models (ASMs) based on 28046 online samples were used for character synthesis and statistical properties were extracted from the IESK-arDB database to simulate baselines and word slant or skew. In the synthesis step ASM based representations are composed to words and text pages, smoothed by B-Spline interpolation and rendered considering writing speed and pen characteristics. Finally, we use the synthetic data to validate a segmentation method. An experimental comparison with the IESK-arDB database encourages to train and test document analysis related methods on synthetic samples, whenever no sufficient natural ground truthed data is available. PMID:26295059

  14. Robust Object Recognition under Partial Occlusions Using NMF

    Directory of Open Access Journals (Sweden)

    Daniel Soukup

    2008-01-01

    Full Text Available In recent years, nonnegative matrix factorization (NMF methods of a reduced image data representation attracted the attention of computer vision community. These methods are considered as a convenient part-based representation of image data for recognition tasks with occluded objects. A novel modification in NMF recognition tasks is proposed which utilizes the matrix sparseness control introduced by Hoyer. We have analyzed the influence of sparseness on recognition rates (RRs for various dimensions of subspaces generated for two image databases, ORL face database, and USPS handwritten digit database. We have studied the behavior of four types of distances between a projected unknown image object and feature vectors in NMF subspaces generated for training data. One of these metrics also is a novelty we proposed. In the recognition phase, partial occlusions in the test images have been modeled by putting two randomly large, randomly positioned black rectangles into each test image.

  15. Cryptographic key generation using handwritten signature

    Science.gov (United States)

    Freire-Santos, M.; Fierrez-Aguilar, J.; Ortega-Garcia, J.

    2006-04-01

    Based on recent works showing the feasibility of key generation using biometrics, we study the application of handwritten signature to cryptography. Our signature-based key generation scheme implements the cryptographic construction named fuzzy vault. The use of distinctive signature features suited for the fuzzy vault is discussed and evaluated. Experimental results are reported, including error rates to unlock the secret data by using both random and skilled forgeries from the MCYT database.

  16. A natural approach to convey numerical digits using hand activity recognition based on hand shape features

    Science.gov (United States)

    Chidananda, H.; Reddy, T. Hanumantha

    2017-06-01

    This paper presents a natural representation of numerical digit(s) using hand activity analysis based on number of fingers out stretched for each numerical digit in sequence extracted from a video. The analysis is based on determining a set of six features from a hand image. The most important features used from each frame in a video are the first fingertip from top, palm-line, palm-center, valley points between the fingers exists above the palm-line. Using this work user can convey any number of numerical digits using right or left or both the hands naturally in a video. Each numerical digit ranges from 0 to9. Hands (right/left/both) used to convey digits can be recognized accurately using the valley points and with this recognition whether the user is a right / left handed person in practice can be analyzed. In this work, first the hand(s) and face parts are detected by using YCbCr color space and face part is removed by using ellipse based method. Then, the hand(s) are analyzed to recognize the activity that represents a series of numerical digits in a video. This work uses pixel continuity algorithm using 2D coordinate geometry system and does not use regular use of calculus, contours, convex hull and datasets.

  17. Evaluation of speech recognition of cochlear implant recipients using a personal digital adaptive radio frequency system.

    Science.gov (United States)

    Wolfe, Jace; Morais, Mila; Schafer, Erin; Mills, Emily; Mülder, Hans E; Goldbeck, Felix; Marquis, Francois; John, Andrew; Hudson, Mary; Peters, B Robert; Lianos, Leslie

    2013-09-01

    Previous research supports the use of frequency modulation (FM) systems for improving speech recognition in noise of individuals with cochlear implants (CIs). However, at this time, there is no published research on the potential speech recognition benefit of new digital adaptive wireless radio transmission systems. The goal of this study was to compare speech recognition in quiet and in noise of CI recipients while using traditional, fixed-gain analog FM systems, adaptive analog FM systems, and adaptive digital wireless radio frequency transmission systems. A three-way repeated-measures design was used to examine performance differences among devices, among speech recognition conditions in quiet and in increasing levels of background noise, and between users of Advanced Bionics and Cochlear CIs. Seventeen users of Advanced Bionics Harmony CI sound processors and 20 users of Cochlear Nucleus 5 sound processors were included in the study. Participants were tested in a total of 32 speech-recognition-in noise-test conditions, which included one no-FM and three device conditions (fixed-gain FM, adaptive FM, and adaptive digital) at the following signal levels: 64 dBA speech (at the location of the participant) in quiet and 64 dBA speech with competing noise at 50, 55, 60, 65, 70, 75, and 80 dBA noise levels. No significant differences were detected between the users of Advanced Bionics and Cochlear CIs. All of the radio frequency system conditions (i.e., fixed-gain FM, adaptive FM, and adaptive digital) outperformed the no-FM conditions in test situations with competing noise. Specifically, in conditions with 70, 75, and 80 dBA of competing noise, the adaptive digital system provided better performance than the fixed-gain and adaptive FM systems. The adaptive FM system did provide better performance than the fixed-gain FM system at 70 and 75 dBA of competing noise. At the lower noise levels of 50, 55, 60, and 65 dBA, no significant differences were detected across the

  18. Segmentation of Arabic Handwritten Documents into Text Lines using Watershed Transform

    Directory of Open Access Journals (Sweden)

    Abdelghani Souhar

    2017-12-01

    Full Text Available A crucial task in character recognition systems is the segmentation of the document into text lines and especially if it is handwritten. When dealing with non-Latin document such as Arabic, the challenge becomes greater since in addition to the variability of writing, the presence of diacritical points and the high number of ascender and descender characters complicates more the process of the segmentation. To remedy with this complexity and even to make this difficulty an advantage since the focus is on the Arabic language which is semi-cursive in nature, a method based on the Watershed Transform technique is proposed. Tested on «Handwritten Arabic Proximity Datasets» a segmentation rate of 93% for a 95% of matching score is achieved.

  19. Automated Fourier space region-recognition filtering for off-axis digital holographic microscopy

    CERN Document Server

    He, Xuefei; Pratap, Mrinalini; Zheng, Yujie; Wang, Yi; Nisbet, David R; Williams, Richard J; Rug, Melanie; Maier, Alexander G; Lee, Woei Ming

    2016-01-01

    Automated label-free quantitative imaging of biological samples can greatly benefit high throughput diseases diagnosis. Digital holographic microscopy (DHM) is a powerful quantitative label-free imaging tool that retrieves structural details of cellular samples non-invasively. In off-axis DHM, a proper spatial filtering window in Fourier space is crucial to the quality of reconstructed phase image. Here we describe a region-recognition approach that combines shape recognition with an iterative thresholding to extracts the optimal shape of frequency components. The region recognition technique offers fully automated adaptive filtering that can operate with a variety of samples and imaging conditions. When imaging through optically scattering biological hydrogel matrix, the technique surpasses previous histogram thresholding techniques without requiring any manual intervention. Finally, we automate the extraction of the statistical difference of optical height between malaria parasite infected and uninfected re...

  20. Environment Recognition for Digital Audio Forensics Using MPEG-7 and MEL Cepstral Features

    Science.gov (United States)

    Muhammad, Ghulam; Alghathbar, Khalid

    2011-07-01

    Environment recognition from digital audio for forensics application is a growing area of interest. However, compared to other branches of audio forensics, it is a less researched one. Especially less attention has been given to detect environment from files where foreground speech is present, which is a forensics scenario. In this paper, we perform several experiments focusing on the problems of environment recognition from audio particularly for forensics application. Experimental results show that the task is easier when audio files contain only environmental sound than when they contain both foreground speech and background environment. We propose a full set of MPEG-7 audio features combined with mel frequency cepstral coefficients (MFCCs) to improve the accuracy. In the experiments, the proposed approach significantly increases the recognition accuracy of environment sound even in the presence of high amount of foreground human speech.

  1. Target recognition and phase acquisition by using incoherent digital holographic imaging

    Science.gov (United States)

    Lee, Munseob; Lee, Byung-Tak

    2017-05-01

    In this study, we proposed the Incoherent Digital Holographic Imaging (IDHI) for recognition and phase information of dedicated target. Although recent development of a number of target recognition techniques such as LIDAR, there have limited success in target discrimination, in part due to low-resolution, low scanning speed, and computation power. In the paper, the proposed system consists of the incoherent light source, such as LED, Michelson interferometer, and digital CCD for acquisition of four phase shifting image. First of all, to compare with relative coherence, we used a source as laser and LED, respectively. Through numerical reconstruction by using the four phase shifting method and Fresnel diffraction method, we recovered the intensity and phase image of USAF resolution target apart from about 1.0m distance. In this experiment, we show 1.2 times improvement in resolution compared to conventional imaging. Finally, to confirm the recognition result of camouflaged targets with the same color from background, we carry out to test holographic imaging in incoherent light. In this result, we showed the possibility of a target detection and recognition that used three dimensional shape and size signatures, numerical distance from phase information of obtained holographic image.

  2. The effects of digital signal processing features on children's speech recognition and loudness perception.

    Science.gov (United States)

    Crukley, Jeffery; Scollie, Susan D

    2014-03-01

    The purpose of this study was to determine the effects of hearing instruments set to Desired Sensation Level version 5 (DSL v5) hearing instrument prescription algorithm targets and equipped with directional microphones and digital noise reduction (DNR) on children's sentence recognition in noise performance and loudness perception in a classroom environment. Ten children (ages 8-17 years) with stable, congenital sensorineural hearing losses participated in the study. Participants were fitted bilaterally with behind-the-ear hearing instruments set to DSL v5 prescriptive targets. Sentence recognition in noise was evaluated using the Bamford-Kowal-Bench Speech in Noise Test (Niquette et al., 2003). Loudness perception was evaluated using a modified version of the Contour Test of Loudness Perception (Cox, Alexander, Taylor, & Gray, 1997). Children's sentence recognition in noise performance was significantly better when using directional microphones alone or in combination with DNR than when using omnidirectional microphones alone or in combination with DNR. Children's loudness ratings for sounds above 72 dB SPL were lowest when fitted with the DSL v5 Noise prescription combined with directional microphones. DNR use showed no effect on loudness ratings. Use of the DSL v5 Noise prescription with a directional microphone improved sentence recognition in noise performance and reduced loudness perception ratings for loud sounds relative to a typical clinical reference fitting with the DSL v5 Quiet prescription with no digital signal processing features enabled. Potential clinical strategies are discussed.

  3. 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.

  4. A Digital Liquid State Machine With Biologically Inspired Learning and Its Application to Speech Recognition.

    Science.gov (United States)

    Zhang, Yong; Li, Peng; Jin, Yingyezhe; Choe, Yoonsuck

    2015-11-01

    This paper presents a bioinspired digital liquid-state machine (LSM) for low-power very-large-scale-integration (VLSI)-based machine learning applications. To the best of the authors' knowledge, this is the first work that employs a bioinspired spike-based learning algorithm for the LSM. With the proposed online learning, the LSM extracts information from input patterns on the fly without needing intermediate data storage as required in offline learning methods such as ridge regression. The proposed learning rule is local such that each synaptic weight update is based only upon the firing activities of the corresponding presynaptic and postsynaptic neurons without incurring global communications across the neural network. Compared with the backpropagation-based learning, the locality of computation in the proposed approach lends itself to efficient parallel VLSI implementation. We use subsets of the TI46 speech corpus to benchmark the bioinspired digital LSM. To reduce the complexity of the spiking neural network model without performance degradation for speech recognition, we study the impacts of synaptic models on the fading memory of the reservoir and hence the network performance. Moreover, we examine the tradeoffs between synaptic weight resolution, reservoir size, and recognition performance and present techniques to further reduce the overhead of hardware implementation. Our simulation results show that in terms of isolated word recognition evaluated using the TI46 speech corpus, the proposed digital LSM rivals the state-of-the-art hidden Markov-model-based recognizer Sphinx-4 and outperforms all other reported recognizers including the ones that are based upon the LSM or neural networks.

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

    Directory of Open Access Journals (Sweden)

    Xingyu Pan

    2017-05-01

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

  6. The Characteristics of Binary Spike-Time-Dependent Plasticity in HfO2-Based RRAM and Applications for Pattern Recognition.

    Science.gov (United States)

    Zhou, Zheng; Liu, Chen; Shen, Wensheng; Dong, Zhen; Chen, Zhe; Huang, Peng; Liu, Lifeng; Liu, Xiaoyan; Kang, Jinfeng

    2017-12-01

    A binary spike-time-dependent plasticity (STDP) protocol based on one resistive-switching random access memory (RRAM) device was proposed and experimentally demonstrated in the fabricated RRAM array. Based on the STDP protocol, a novel unsupervised online pattern recognition system including RRAM synapses and CMOS neurons is developed. Our simulations show that the system can efficiently compete the handwritten digits recognition task, which indicates the feasibility of using the RRAM-based binary STDP protocol in neuromorphic computing systems to obtain good performance.

  7. Assessment of legibility and completeness of handwritten and electronic prescriptions

    Science.gov (United States)

    Albarrak, Ahmed I; Al Rashidi, Eman Abdulrahman; Fatani, Rwaa Kamil; Al Ageel, Shoog Ibrahim; Mohammed, Rafiuddin

    2014-01-01

    Objectives To assess the legibility and completeness of handwritten prescriptions and compare with electronic prescription system for medication errors. Design Prospective study. Setting King Khalid University Hospital (KKUH), Riyadh, Saudi Arabia. Subjects and methods Handwritten prescriptions were received from clinical units of Medicine Outpatient Department (MOPD), Primary Care Clinic (PCC) and Surgery Outpatient Department (SOPD) whereas electronic prescriptions were collected from the pediatric ward. The handwritten prescription was assessed for completeness by the checklist designed according to the hospital prescription and evaluated for legibility by two pharmacists. The comparison between handwritten and electronic prescription errors was evaluated based on the validated checklist adopted from previous studies. Main outcome measures Legibility and completeness of prescriptions. Results 398 prescriptions (199 handwritten and 199 e-prescriptions) were assessed. About 71 (35.7%) of handwritten and 5 (2.5%) of electronic prescription errors were identified. A significant statistical difference (P prescriptions in omitted dose and omitted route of administration category of error distribution. The rate of completeness in patient identification in handwritten prescriptions was 80.97% in MOPD, 76.36% in PCC and 85.93% in SOPD clinic units. Assessment of medication prescription completeness was 91.48% in MOPD, 88.48% in PCC, and 89.28% in SOPD. Conclusions This study revealed a high incidence of prescribing errors in handwritten prescriptions. The use of e-prescription system showed a significant decline in the incidence of errors. The legibility of handwritten prescriptions was relatively good whereas the level of completeness was very low. PMID:25561864

  8. The application of digital image recognition to the analysis of two-dimensional fingerprints.

    Science.gov (United States)

    Zhai, Hong Lin; Hu, Fang Di; Huang, Xiao Yan; Chen, Jun Hui

    2010-01-11

    High-performance liquid chromatography (HPLC) fingerprint has been commonly used in the quality control and assessment of herbal medicines, and two-dimensional (2D) fingerprint obtained by means of HPLC-diode array detector (HPLC/DAD) can provide higher reliability. In this paper, an approach to the analysis of the 2D HPLC/DAD fingerprints, which was based on digital image recognition techniques, was developed for the first time. First, wavelet transform was employed to eliminate noise signal in the 2D fingerprint, and then the 2D fingerprint was converted into grayscale image. Second, several features of the image were calculated, and hierarchical clustering. This approach was applied to the qualitative analysis of the different samples of coptis chinensis, and the clustering result of samples was all highly consistent with the real situation. Based on the densities in grayscale image, three components in standard samples were quantitative analyzed, and the obtained correlation coefficients between concentration and grayscale density were more than 0.999. Our study indicated that the analysis of the 2D HPLC/DAD fingerprint was successful based on the idea and techniques of digital image recognition techniques, and this proposed approach provided a new pathway for the analysis of two-dimensional spectrums.

  9. Formant analysis in dysphonic patients and automatic Arabic digit speech recognition.

    Science.gov (United States)

    Muhammad, Ghulam; Mesallam, Tamer A; Malki, Khalid H; Farahat, Mohamed; Alsulaiman, Mansour; Bukhari, Manal

    2011-05-30

    There has been a growing interest in objective assessment of speech in dysphonic patients for the classification of the type and severity of voice pathologies using automatic speech recognition (ASR). The aim of this work was to study the accuracy of the conventional ASR system (with Mel frequency cepstral coefficients (MFCCs) based front end and hidden Markov model (HMM) based back end) in recognizing the speech characteristics of people with pathological voice. The speech samples of 62 dysphonic patients with six different types of voice disorders and 50 normal subjects were analyzed. The Arabic spoken digits were taken as an input. The distribution of the first four formants of the vowel /a/ was extracted to examine deviation of the formants from normal. There was 100% recognition accuracy obtained for Arabic digits spoken by normal speakers. However, there was a significant loss of accuracy in the classifications while spoken by voice disordered subjects. Moreover, no significant improvement in ASR performance was achieved after assessing a subset of the individuals with disordered voices who underwent treatment. The results of this study revealed that the current ASR technique is not a reliable tool in recognizing the speech of dysphonic patients.

  10. Formant analysis in dysphonic patients and automatic Arabic digit speech recognition

    Directory of Open Access Journals (Sweden)

    Farahat Mohamed

    2011-05-01

    Full Text Available Abstract Background and objective There has been a growing interest in objective assessment of speech in dysphonic patients for the classification of the type and severity of voice pathologies using automatic speech recognition (ASR. The aim of this work was to study the accuracy of the conventional ASR system (with Mel frequency cepstral coefficients (MFCCs based front end and hidden Markov model (HMM based back end in recognizing the speech characteristics of people with pathological voice. Materials and methods The speech samples of 62 dysphonic patients with six different types of voice disorders and 50 normal subjects were analyzed. The Arabic spoken digits were taken as an input. The distribution of the first four formants of the vowel /a/ was extracted to examine deviation of the formants from normal. Results There was 100% recognition accuracy obtained for Arabic digits spoken by normal speakers. However, there was a significant loss of accuracy in the classifications while spoken by voice disordered subjects. Moreover, no significant improvement in ASR performance was achieved after assessing a subset of the individuals with disordered voices who underwent treatment. Conclusion The results of this study revealed that the current ASR technique is not a reliable tool in recognizing the speech of dysphonic patients.

  11. Permutation coding technique for image recognition systems.

    Science.gov (United States)

    Kussul, Ernst M; Baidyk, Tatiana N; Wunsch, Donald C; Makeyev, Oleksandr; Martín, Anabel

    2006-11-01

    A feature extractor and neural classifier for image recognition systems are proposed. The proposed feature extractor is based on the concept of random local descriptors (RLDs). It is followed by the encoder that is based on the permutation coding technique that allows to take into account not only detected features but also the position of each feature on the image and to make the recognition process invariant to small displacements. The combination of RLDs and permutation coding permits us to obtain a sufficiently general description of the image to be recognized. The code generated by the encoder is used as an input data for the neural classifier. Different types of images were used to test the proposed image recognition system. It was tested in the handwritten digit recognition problem, the face recognition problem, and the microobject shape recognition problem. The results of testing are very promising. The error rate for the Modified National Institute of Standards and Technology (MNIST) database is 0.44% and for the Olivetti Research Laboratory (ORL) database it is 0.1%.

  12. Use of digital speech recognition in diagnostics radiology; Anwendung der digitalen Spracherkennung in der radiologischen Routine

    Energy Technology Data Exchange (ETDEWEB)

    Arndt, H.; Stockheim, D.; Mutze, S. [Unfallkrankenhaus Berlin, Krankenhaus Berlin-Marzahn mit Berufsgenossenschaftlicher Unfallklinik e.V., Inst. fuer Radiologie (Germany); Petersein, J.; Gregor, P.; Hamm, B. [Universitaetsklinikum Charite, Medizinische Fakultaet, Humboldt-Univ. Berlin, Campus Charite Mitte, Inst. fuer Roentgendiagnostik (Germany)

    1999-11-01

    Purpose: Applicability and benefits of digital speech recognition in diagnostic radiology were tested using the speech recognition system SP 6000. Methods: The speech recognition system SP 6000 was integrated into the network of the institute and connected to the existing Radiological Information System (RIS). Three subjects used this system for writing 2305 findings from dictation. After the recognition process the date, length of dictation, time required for checking/correction, kind of examination and error rate were recorded for every dictation. With the same subjects, a correlation was performed with 625 conventionally written finding. Results: After an 1-hour initial training the average error rates were 8.4 to 13.3%. The first adaptation of the speech recognition system (after nine days) decreased the average error rates to 2.4 to 10.7% due to the ability of the program to learn. The 2{sup nd} and 3{sup rd} adaptations resulted only in small changes of the error rate. An individual comparison of the error rate developments in the same kind of investigation showed the relative independence of the error rate on the individual user. Conclusion: The results show that the speech recognition system SP 6000 can be evaluated as an advantageous alternative for quickly recording radiological findings. A comparison between manually writing and dictating the findings verifies the individual differences of the writing speeds and shows the advantage of the application of voice recognition when faced with normal keyboard performance. (orig.) [German] Ziel: Die Einsetzbarkeit und der Nutzen der digitalen Sprachkerkennung in der radiologischen Diagnostik soll anhand des Spracherkennungssystems SP 6000 getestet werden. Methodik: Das Spracherkennungssystem SP 6000 wurde in das Institutsnetzwerk integriert und an das vorhandene Radiologische Informationssystem (RIS) angebunden. Drei Testpersonen nutzten bei 2305 Diktaten dieses System zur Befunderstellung. Es wurden Datum

  13. A novel handwritten character recognition system using gradient ...

    Indian Academy of Sciences (India)

    Author Affiliations. G Raju1 Bindu S Moni2 Madhu S Nair3. Department of Information Technology, Kannur University, Kannur 670 567, India; School of Computer Sciences, Mahatma Gandhi University, Kottayam 686 560, India; Department of Computer Science, University of Kerala, Kariavattom, Thiruvananthapuram 695 ...

  14. Recognition of online handwritten Gurmukhi characters based on ...

    Indian Academy of Sciences (India)

    Headline and baseline are common features in most Indic languages which divide a character into three zones, namely, upper, middle andlower zones. Identification of headline and ... A rule-based approach has also been applied and tested for generation of characters from the set of recognized strokes. In this work, an ...

  15. A knowledge-based approach for recognition of handwritten Pitman ...

    Indian Academy of Sciences (India)

    The Pitman shorthand language (PSL) is a recording medium practised in all organizations, where English is the transaction medium. It has the practical advantage of high speed of recording, more than 120-200 words per minute, because of which it is universally acknowledged. This recording medium has its continued ...

  16. A knowledge-based approach for recognition of handwritten Pitman ...

    Indian Academy of Sciences (India)

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

    MS received 6 November 2000; revised 20 November 2001. Abstract. The Pitman shorthand language (PSL) is a recording medium practised in all organizations, where English is the transaction medium. It has the practi- cal advantage of high speed of recording, more than 120–200 words per minute, because of which it is ...

  17. Segmentation-free Word Spotting for Handwritten Arabic Documents

    National Research Council Canada - National Science Library

    Ghizlane Khaissidi; Youssef Elfakir; Mostafa Mrabti; Mounîm El Yacoubi; Driss Chenouni; Zakia Lakhliai

    2016-01-01

    In this paper we present an unsupervised segmentation-free method for spotting and searching query, especially, for images documents in handwritten Arabic, for this, Histograms of Oriented Gradients (HOGs...

  18. Digital field mapping for stimulating Secondary School students in the recognition of geological features and landforms

    Science.gov (United States)

    Giardino, Marco; Magagna, Alessandra; Ferrero, Elena; Perrone, Gianluigi

    2015-04-01

    Digital field mapping has certainly provided geoscientists with the opportunity to map and gather data in the field directly using digital tools and software rather than using paper maps, notebooks and analogue devices and then subsequently transferring the data to a digital format for subsequent analysis. But, the same opportunity has to be recognized for Geoscience education, as well as for stimulating and helping students in the recognition of landforms and interpretation of the geological and geomorphological components of a landscape. More, an early exposure to mapping during school and prior to university can optimise the ability to "read" and identify uncertainty in 3d models. During 2014, about 200 Secondary School students (aged 12-15) of the Piedmont region (NW Italy) participated in a research program involving the use of mobile devices (smartphone and tablet) in the field. Students, divided in groups, used the application Trimble Outdoors Navigators for tracking a geological trail in the Sangone Valley and for taking georeferenced pictures and notes. Back to school, students downloaded the digital data in a .kml file for the visualization on Google Earth. This allowed them: to compare the hand tracked trail on a paper map with the digital trail, and to discuss about the functioning and the precision of the tools; to overlap a digital/semitransparent version of the 2D paper map (a Regional Technical Map) used during the field trip on the 2.5D landscape of Google Earth, as to help them in the interpretation of conventional symbols such as contour lines; to perceive the landforms seen during the field trip as a part of a more complex Pleistocene glacial landscape; to understand the classical and innovative contributions from different geoscientific disciplines to the generation of a 3D structural geological model of the Rivoli-Avigliana Morainic Amphitheatre. In 2013 and 2014, some other pilot projects have been carried out in different areas of the

  19. Estimation of the Handwritten Text Skew Based on Binary Moments

    OpenAIRE

    D. Brodić, Z. Milivojević

    2012-01-01

    Binary moments represent one of the methods for the text skew estimation in binary images. It has been used widely for the skew identification of the printed text. However, the handwritten text consists of text objects, which are characterized with different skews. Hence, the method should be adapted for the handwritten text. This is achieved with the image splitting into separate text objects made by the bounding boxes. Obtained text objects represent the isolated binary objects. The applica...

  20. Optical and digital pattern recognition; Proceedings of the Meeting, Los Angeles, CA, Jan. 13-15, 1987

    Science.gov (United States)

    Liu, Hua-Kuang (Editor); Schenker, Paul (Editor)

    1987-01-01

    The papers presented in this volume provide an overview of current research in both optical and digital pattern recognition, with a theme of identifying overlapping research problems and methodologies. Topics discussed include image analysis and low-level vision, optical system design, object analysis and recognition, real-time hybrid architectures and algorithms, high-level image understanding, and optical matched filter design. Papers are presented on synthetic estimation filters for a control system; white-light correlator character recognition; optical AI architectures for intelligent sensors; interpreting aerial photographs by segmentation and search; and optical information processing using a new photopolymer.

  1. Digital Technologies for Social Innovation: An Empirical Recognition on the New Enablers

    Directory of Open Access Journals (Sweden)

    Riccardo Maiolini

    2016-12-01

    Full Text Available Even though scholars’ attention has been placed on Social Innovation (SI, little evidence has been provided with regards to which tools are actually used to address social needs and foster Social Innovation initiatives. The purpose of the article is twofold. Firstly, the article offers empirical recognition to SI by investigating, on a large-scale, social and innovative activities conducted by start-ups and small and medium-sized enterprises (SMEs across the world between 2001 and 2014. Secondly, the article intends to capture SI core businesses and underlying complementarities between products, markets, and technologies and show in which way digital media and IT are essentially tracing innovation trajectories over a multitude of industries, leading the current industrial patterns of SI, and continually fostering its cross-industry nature.

  2. Recognition of materials and damage on historical buildings using digital image classification

    Directory of Open Access Journals (Sweden)

    Jose E. Merono

    2015-01-01

    Full Text Available Nowadays, techniques in digital image processing make it possible to detect damage, such as moisture or biological changes, on the surfaces of historical buildings. Digital classification techniques can be used to identify damages in construction materials in a non-destructive way. In this study, we evaluate the application of the object-oriented classification technique using photographs taken with a Fujifilm IS-Pro digital single lens reflex camera and the integration of the classified images in a three-dimensional model obtained through terrestrial laser scanning data in order to detect and locate damage affecting biocalcarenite stone employed in the construction of the Santa Marina Church (Córdoba, Spain. The Fujifilm IS-Pro camera captures spectral information in an extra-visible range, generating a wide spectral image with wavelengths ranging from ultraviolet to infrared. Techniques of object-oriented classification were applied, taking into account the shapes, textures, background information and spectral information in the image. This type of classification requires prior segmentation, defined as the search for homogeneous regions in an image. The second step is the classification process of these regions based on examples. The output data were classified according to the kind of damage that affects the biocalcarenite stone, reaching an overall classification accuracy of 92% and an excellent kappa statistic (85.7%. We have shown that multispectral classification with visible and near-infrared bands increased the degree of recognition among different damages. Post-analysis of these data integrated in a three-dimensional model allows us to obtain thematic maps with the size and position of the damage.

  3. Comparison of speech recognition with adaptive digital and FM remote microphone hearing assistance technology by listeners who use hearing aids.

    Science.gov (United States)

    Thibodeau, Linda

    2014-06-01

    The purpose of this study was to compare the benefits of 3 types of remote microphone hearing assistance technology (HAT), adaptive digital broadband, adaptive frequency modulation (FM), and fixed FM, through objective and subjective measures of speech recognition in clinical and real-world settings. Participants included 11 adults, ages 16 to 78 years, with primarily moderate-to-severe bilateral hearing impairment (HI), who wore binaural behind-the-ear hearing aids; and 15 adults, ages 18 to 30 years, with normal hearing. Sentence recognition in quiet and in noise and subjective ratings were obtained in 3 conditions of wireless signal processing. Performance by the listeners with HI when using the adaptive digital technology was significantly better than that obtained with the FM technology, with the greatest benefits at the highest noise levels. The majority of listeners also preferred the digital technology when listening in a real-world noisy environment. The wireless technology allowed persons with HI to surpass persons with normal hearing in speech recognition in noise, with the greatest benefit occurring with adaptive digital technology. The use of adaptive digital technology combined with speechreading cues would allow persons with HI to engage in communication in environments that would have otherwise not been possible with traditional wireless technology.

  4. Novel Blind Recognition Algorithm of Frame Synchronization Words Based on Soft-Decision in Digital Communication Systems.

    Directory of Open Access Journals (Sweden)

    Jiangyi Qin

    Full Text Available A novel blind recognition algorithm of frame synchronization words is proposed to recognize the frame synchronization words parameters in digital communication systems. In this paper, a blind recognition method of frame synchronization words based on the hard-decision is deduced in detail. And the standards of parameter recognition are given. Comparing with the blind recognition based on the hard-decision, utilizing the soft-decision can improve the accuracy of blind recognition. Therefore, combining with the characteristics of Quadrature Phase Shift Keying (QPSK signal, an improved blind recognition algorithm based on the soft-decision is proposed. Meanwhile, the improved algorithm can be extended to other signal modulation forms. Then, the complete blind recognition steps of the hard-decision algorithm and the soft-decision algorithm are given in detail. Finally, the simulation results show that both the hard-decision algorithm and the soft-decision algorithm can recognize the parameters of frame synchronization words blindly. What's more, the improved algorithm can enhance the accuracy of blind recognition obviously.

  5. Novel Blind Recognition Algorithm of Frame Synchronization Words Based on Soft-Decision in Digital Communication Systems.

    Science.gov (United States)

    Qin, Jiangyi; Huang, Zhiping; Liu, Chunwu; Su, Shaojing; Zhou, Jing

    2015-01-01

    A novel blind recognition algorithm of frame synchronization words is proposed to recognize the frame synchronization words parameters in digital communication systems. In this paper, a blind recognition method of frame synchronization words based on the hard-decision is deduced in detail. And the standards of parameter recognition are given. Comparing with the blind recognition based on the hard-decision, utilizing the soft-decision can improve the accuracy of blind recognition. Therefore, combining with the characteristics of Quadrature Phase Shift Keying (QPSK) signal, an improved blind recognition algorithm based on the soft-decision is proposed. Meanwhile, the improved algorithm can be extended to other signal modulation forms. Then, the complete blind recognition steps of the hard-decision algorithm and the soft-decision algorithm are given in detail. Finally, the simulation results show that both the hard-decision algorithm and the soft-decision algorithm can recognize the parameters of frame synchronization words blindly. What's more, the improved algorithm can enhance the accuracy of blind recognition obviously.

  6. A Hierarchical Predictive Coding Model of Object Recognition in Natural Images.

    Science.gov (United States)

    Spratling, M W

    2017-01-01

    Predictive coding has been proposed as a model of the hierarchical perceptual inference process performed in the cortex. However, results demonstrating that predictive coding is capable of performing the complex inference required to recognise objects in natural images have not previously been presented. This article proposes a hierarchical neural network based on predictive coding for performing visual object recognition. This network is applied to the tasks of categorising hand-written digits, identifying faces, and locating cars in images of street scenes. It is shown that image recognition can be performed with tolerance to position, illumination, size, partial occlusion, and within-category variation. The current results, therefore, provide the first practical demonstration that predictive coding (at least the particular implementation of predictive coding used here; the PC/BC-DIM algorithm) is capable of performing accurate visual object recognition.

  7. Unsupervised Learning of Digit Recognition Using Spike-Timing-Dependent Plasticity

    Directory of Open Access Journals (Sweden)

    Peter U. Diehl

    2015-08-01

    Full Text Available In order to understand how the mammalian neocortex is performing computations, two things are necessary; we need to have a good understanding of the available neuronal processing units and mechanisms, and we need to gain a better understanding of how those mechanisms are combined to build functioning systems. Therefore, in recent years there is an increasing interest in how spiking neural networks (SNN can be used to perform complex computations or solve pattern recognition tasks. However, it remains a challenging task to design SNNs which use biologically plausible mechanisms (especially for learning new patterns, since most of such SNN architectures rely on training in a rate-based network and subsequent conversion to a SNN. We present a SNN for digit recognition which is based on mechanisms with increased biological plausibility, i.e. conductance-based instead of current-based synapses, spike-timing-dependent plasticity with time-dependent weight change, lateral inhibition, and an adaptive spiking threshold. Unlike most other systems, we do not use a teaching signal and do not present any class labels to the network. Using this unsupervised learning scheme, our architecture achieves 95% accuracy on the MNIST benchmark, which is better than previous SNN implementations without supervision. The fact that we used no domain-specific knowledge points toward the general applicability of our network design. Also, the performance of our network scales well with the number of neurons used and shows similar performance for four different learning rules, indicating robustness of the full combination of mechanisms, which suggests applicability in heterogeneous biological neural networks.

  8. An efficient method to enhance the readability of historical handwritten artifacts

    Science.gov (United States)

    Soni, Ramakant; Shekhawat, Pradeep Singh; Jangir, Ramesh; Saini, Sanjay Kumar

    2016-03-01

    Historical handwritten letters, manuscripts, old books, paintings and similar artifacts are extremely valuable heritage and of historical importance. During a course of time these are subjected to various degradation factors which reduce their visual quality and degrade state. To preserve these for future generation their digitization is the best suitable method. Converting these into digital format will enhance their state in terms of visual quality. Using various image processing and analysis techniques their state and quality can be enhanced which will help us to restore them and preserve them and analyze them to explore valuable information of the past. This paper is based on combining different image processing techniques like de-noising the images and making them smoother, de-blurring the motion blur effects and reducing the intensity levels to reduce the memory consumption.

  9. Latent log-linear models for handwritten digit classification.

    Science.gov (United States)

    Deselaers, Thomas; Gass, Tobias; Heigold, Georg; Ney, Hermann

    2012-06-01

    We present latent log-linear models, an extension of log-linear models incorporating latent variables, and we propose two applications thereof: log-linear mixture models and image deformation-aware log-linear models. The resulting models are fully discriminative, can be trained efficiently, and the model complexity can be controlled. Log-linear mixture models offer additional flexibility within the log-linear modeling framework. Unlike previous approaches, the image deformation-aware model directly considers image deformations and allows for a discriminative training of the deformation parameters. Both are trained using alternating optimization. For certain variants, convergence to a stationary point is guaranteed and, in practice, even variants without this guarantee converge and find models that perform well. We tune the methods on the USPS data set and evaluate on the MNIST data set, demonstrating the generalization capabilities of our proposed models. Our models, although using significantly fewer parameters, are able to obtain competitive results with models proposed in the literature.

  10. Handwritten Newspapers on the Iowa Frontier, 1844-54.

    Science.gov (United States)

    Atwood, Roy Alden

    Journalism on the agricultural frontier of the Old Northwest territory of the United States was shaped by a variety of cultural forces and environmental factors and took on diverse forms. Bridging the gap between the two cultural forms of written correspondence and printed news was a third form: the handwritten newspaper. Between 1844 and 1854…

  11. Spelling Correlation on Handwritten vs. Multiple-Choice Tests.

    Science.gov (United States)

    Kelso, Genell

    In order to determine if multiple choice spelling tests are as effective as handwritten tests, 265 college freshmen were tested on the same spelling words by traditional oral dictation and then by five-option multiple choice questions. Results were compared to examine the efficacy of multiple choice testing. Of a possible 20 points, the mean score…

  12. Two-tier architecture for unconstrained handwritten character ...

    Indian Academy of Sciences (India)

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

    e-mail:{prema−kv, dr−nvsreddy}@rediffmail.com. Abstract. In this paper, we propose an approach that combines the unsupervised and supervised learning techniques for unconstrained handwritten numeral recog- nition. This approach uses the Kohonen self-organizing neural network for data classification in the first stage ...

  13. Neuromorphic Hardware Architecture Using the Neural Engineering Framework for Pattern Recognition.

    Science.gov (United States)

    Wang, Runchun; Thakur, Chetan Singh; Cohen, Gregory; Hamilton, Tara Julia; Tapson, Jonathan; van Schaik, Andre

    2017-06-01

    We present a hardware architecture that uses the neural engineering framework (NEF) to implement large-scale neural networks on field programmable gate arrays (FPGAs) for performing massively parallel real-time pattern recognition. NEF is a framework that is capable of synthesising large-scale cognitive systems from subnetworks and we have previously presented an FPGA implementation of the NEF that successfully performs nonlinear mathematical computations. That work was developed based on a compact digital neural core, which consists of 64 neurons that are instantiated by a single physical neuron using a time-multiplexing approach. We have now scaled this approach up to build a pattern recognition system by combining identical neural cores together. As a proof of concept, we have developed a handwritten digit recognition system using the MNIST database and achieved a recognition rate of 96.55%. The system is implemented on a state-of-the-art FPGA and can process 5.12 million digits per second. The architecture and hardware optimisations presented offer high-speed and resource-efficient means for performing high-speed, neuromorphic, and massively parallel pattern recognition and classification tasks.

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

    Directory of Open Access Journals (Sweden)

    Antonio Oliver

    2009-01-01

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

  15. Digital-forensics based pattern recognition for discovering identities in electronic evidence

    NARCIS (Netherlands)

    Henseler, Hans; Hofsté, Jop; van Keulen, Maurice

    With the pervasiveness of computers and mobile devices, digital forensics becomes more important in law enforcement. Detectives increasingly depend on the scarce support of digital specialists which impedes efficiency of criminal investigations. This paper proposes and algorithm to extract, merge

  16. Recognizing online Arabic handwritten characters using a deep architecture

    Science.gov (United States)

    Tagougui, Najiba; Kherallah, Monji

    2017-03-01

    Recognizing the online Arabic handwritten script has been gaining more interest because of the impressive advances in mobile device requiring more and more intelligent handwritten recognizers. Since it was demonstrated within many previous research that Deep Neural Networks (DNN) exhibit a great performance, we propose in this work a new system based on a DNN in which we try to optimize the training process by a smooth construct of the deep architecture. The Output's error of each unit in the previous layer will be computed and only the smallest error will be maintained in the next iteration. This paper uses LMCA database for training and testing data. The experimental study reveals that our proposed DBNN using generated Bottleneck features can outperform state of the art online recognizers.

  17. Modeling the lexical morphology of Western handwritten signatures.

    Science.gov (United States)

    Diaz-Cabrera, Moises; Ferrer, Miguel A; Morales, Aythami

    2015-01-01

    A handwritten signature is the final response to a complex cognitive and neuromuscular process which is the result of the learning process. Because of the many factors involved in signing, it is possible to study the signature from many points of view: graphologists, forensic experts, neurologists and computer vision experts have all examined them. Researchers study written signatures for psychiatric, penal, health and automatic verification purposes. As a potentially useful, multi-purpose study, this paper is focused on the lexical morphology of handwritten signatures. This we understand to mean the identification, analysis, and description of the signature structures of a given signer. In this work we analyze different public datasets involving 1533 signers from different Western geographical areas. Some relevant characteristics of signature lexical morphology have been selected, examined in terms of their probability distribution functions and modeled through a General Extreme Value distribution. This study suggests some useful models for multi-disciplinary sciences which depend on handwriting signatures.

  18. IMPROVEMENT OF RECOGNITION QUALITY IN DEEP LEARNING NETWORKS BY SIMULATED ANNEALING METHOD

    Directory of Open Access Journals (Sweden)

    A. S. Potapov

    2014-09-01

    Full Text Available The subject of this research is deep learning methods, in which automatic construction of feature transforms is taken place in tasks of pattern recognition. Multilayer autoencoders have been taken as the considered type of deep learning networks. Autoencoders perform nonlinear feature transform with logistic regression as an upper classification layer. In order to verify the hypothesis of possibility to improve recognition rate by global optimization of parameters for deep learning networks, which are traditionally trained layer-by-layer by gradient descent, a new method has been designed and implemented. The method applies simulated annealing for tuning connection weights of autoencoders while regression layer is simultaneously trained by stochastic gradient descent. Experiments held by means of standard MNIST handwritten digit database have shown the decrease of recognition error rate from 1.1 to 1.5 times in case of the modified method comparing to the traditional method, which is based on local optimization. Thus, overfitting effect doesn’t appear and the possibility to improve learning rate is confirmed in deep learning networks by global optimization methods (in terms of increasing recognition probability. Research results can be applied for improving the probability of pattern recognition in the fields, which require automatic construction of nonlinear feature transforms, in particular, in the image recognition. Keywords: pattern recognition, deep learning, autoencoder, logistic regression, simulated annealing.

  19. Segmentation-free Word Spotting for Handwritten Arabic Documents

    Directory of Open Access Journals (Sweden)

    Ghizlane Khaissidi

    2016-09-01

    Full Text Available In this paper we present an unsupervised segmentation-free method for spotting and searching query, especially, for images documents in handwritten Arabic, for this, Histograms of Oriented Gradients (HOGs are used as the feature vectors to represent the query and documents image. Then, we compress the descriptors with the product quantization method. Finally, a better representation of the query is obtained by using the Support Vector Machines (SVM.

  20. Modeling the Lexical Morphology of Western Handwritten Signatures

    OpenAIRE

    Moises Diaz-Cabrera; Ferrer, Miguel A.; Aythami Morales

    2015-01-01

    A handwritten signature is the final response to a complex cognitive and neuromuscular process which is the result of the learning process. Because of the many factors involved in signing, it is possible to study the signature from many points of view: graphologists, forensic experts, neurologists and computer vision experts have all examined them. Researchers study written signatures for psychiatric, penal, health and automatic verification purposes. As a potentially useful, multi-purpose st...

  1. Handwritten Miscellanies About Peter the Great: Codicological Problems

    Directory of Open Access Journals (Sweden)

    Tatyana A. Bazarova

    2017-09-01

    Full Text Available The readings on the history of Peter’s time seem to be quite stable. These included works written in Petrine time, some of which were published in the first quarter of the 18th century, the chronological tables of Peter the Great’s reign, often with a poetic preface, as well as biographical works by P.N. Krekshin and A. Katiforo, created in Elizabethan time and distributed as copies. The first biographical works about the tsar-reformer were often supplemented by handwritten copies of printed decrees, communiques, letters and other documents. In addition, handwritten miscellanies, consisting exclusively of letters and decrees of Peter the Great, were distributed. In the late 18th – early 19th century handwritten miscellanies about Peter the Great became a subject of interest among collectors and academics. Therefore, at present, these manuscripts can be found in various collections in archives and libraries. The collection’s being part of the family fund gives the researcher an opportunity to talk more confidently about owner and the purposes of compilation. The collections lack necessary historical convoy, and it is very difficult to trace the origin of the manuscript. Codicological research provides an opportunity to clarify the origin, the sociocultural milieu and the further archival being of the miscellanies about Peter the Great.

  2. Devnagari numeral recognition by combining decision of multiple ...

    Indian Academy of Sciences (India)

    The basic objective of the present work is to provide an efficient and reliable technique for recognition of handwritten numerals. Three different types of features have been used for classification of numerals. A multi-classifier connectionist architecture has been proposed for increasing reliability of the recognition results.

  3. Automated Categorization Scheme for Digital Libraries in Distance Learning: A Pattern Recognition Approach

    Science.gov (United States)

    Gunal, Serkan

    2008-01-01

    Digital libraries play a crucial role in distance learning. Nowadays, they are one of the fundamental information sources for the students enrolled in this learning system. These libraries contain huge amount of instructional data (text, audio and video) offered by the distance learning program. Organization of the digital libraries is…

  4. 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.

  5. Digital-forensics based pattern recognition for discovering identities in electronic evidence

    OpenAIRE

    Henseler, Hans; Hofsté, Jop; Keulen, Maurice,

    2013-01-01

    With the pervasiveness of computers and mobile devices, digital forensics becomes more important in law enforcement. Detectives increasingly depend on the scarce support of digital specialists which impedes efficiency of criminal investigations. This paper proposes and algorithm to extract, merge and rank identities that are encountered in the electronic evidence during processing. Two experiments are described demonstrating that our approach can assist with the identification of frequently o...

  6. Computer-implemented land use classification with pattern recognition software and ERTS digital data. [Mississippi coastal plains

    Science.gov (United States)

    Joyce, A. T.

    1974-01-01

    Significant progress has been made in the classification of surface conditions (land uses) with computer-implemented techniques based on the use of ERTS digital data and pattern recognition software. The supervised technique presently used at the NASA Earth Resources Laboratory is based on maximum likelihood ratioing with a digital table look-up approach to classification. After classification, colors are assigned to the various surface conditions (land uses) classified, and the color-coded classification is film recorded on either positive or negative 9 1/2 in. film at the scale desired. Prints of the film strips are then mosaicked and photographed to produce a land use map in the format desired. Computer extraction of statistical information is performed to show the extent of each surface condition (land use) within any given land unit that can be identified in the image. Evaluations of the product indicate that classification accuracy is well within the limits for use by land resource managers and administrators. Classifications performed with digital data acquired during different seasons indicate that the combination of two or more classifications offer even better accuracy.

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

    Science.gov (United States)

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

    2017-05-01

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

  8. Dual function seal: visualized digital signature for electronic medical record systems.

    Science.gov (United States)

    Yu, Yao-Chang; Hou, Ting-Wei; Chiang, Tzu-Chiang

    2012-10-01

    Digital signature is an important cryptography technology to be used to provide integrity and non-repudiation in electronic medical record systems (EMRS) and it is required by law. However, digital signatures normally appear in forms unrecognizable to medical staff, this may reduce the trust from medical staff that is used to the handwritten signatures or seals. Therefore, in this paper we propose a dual function seal to extend user trust from a traditional seal to a digital signature. The proposed dual function seal is a prototype that combines the traditional seal and digital seal. With this prototype, medical personnel are not just can put a seal on paper but also generate a visualized digital signature for electronic medical records. Medical Personnel can then look at the visualized digital signature and directly know which medical personnel generated it, just like with a traditional seal. Discrete wavelet transform (DWT) is used as an image processing method to generate a visualized digital signature, and the peak signal to noise ratio (PSNR) is calculated to verify that distortions of all converted images are beyond human recognition, and the results of our converted images are from 70 dB to 80 dB. The signature recoverability is also tested in this proposed paper to ensure that the visualized digital signature is verifiable. A simulated EMRS is implemented to show how the visualized digital signature can be integrity into EMRS.

  9. 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.

  10. Effect of multichannel digital signal processing on loudness comfort, sentence recognition, and sound quality.

    Science.gov (United States)

    Mispagel, Karen M; Valente, Michael

    2006-01-01

    This study evaluated the effect of increasing the number of processing channels from 32- to 64-signal processing channels on subjects' loudness comfort and satisfaction, sentence recognition, and sound quality of his or her own voice. Ten experienced hearing aid users with mild-to-moderate sensorineural hearing loss wore behind-the-ear (BTE) hearing aids with Adaptive Dynamic Range Optimization (ADRO) signal processing for a period of six weeks in the 32-channel and 64-channel conditions. Results revealed no significant differences in loudness comfort or satisfaction for the majority of sound samples as measured by the Subjective Loudness Test and Environmental Sounds Questionnaire. No significant differences in sentence recognition between the two processing conditions were found as measured by the Hearing In Noise Test (HINT). Additionally, no subjective differences in sound quality of subjects' own voice were determined by the Listening Tasks Questionnaire.

  11. Improving early recognition of malignant melanomas by digital image analysis in dermatoscopy.

    Science.gov (United States)

    Horsch, A; Stolz, W; Neiss, A; Abmayr, W; Pompl, R; Bernklau, A; Bunk, W; Dersch, D R; Glässl, A; Schiffner, R; Morfill, G

    1997-01-01

    The malignant melanoma (MM) is the most dangerous human skin disease. The incidence increased dramatically during the last years. The only chance for the patient is an early recognition and excision of the MM. The best diagnostic method for this is skin surface microscopy or dermatoscopy. Its use, however, requires much expertise. In order to support learning and using the method, a computer-based dermatoscopy workstation is being developed. Among others, new complexity measures are used for the image analysis.

  12. Primary Stability Recognition of the Newly Designed Cementless Femoral Stem Using Digital Signal Processing

    Directory of Open Access Journals (Sweden)

    Mohd Yusof Baharuddin

    2014-01-01

    Full Text Available Stress shielding and micromotion are two major issues which determine the success of newly designed cementless femoral stems. The correlation of experimental validation with finite element analysis (FEA is commonly used to evaluate the stress distribution and fixation stability of the stem within the femoral canal. This paper focused on the applications of feature extraction and pattern recognition using support vector machine (SVM to determine the primary stability of the implant. We measured strain with triaxial rosette at the metaphyseal region and micromotion with linear variable direct transducer proximally and distally using composite femora. The root mean squares technique is used to feed the classifier which provides maximum likelihood estimation of amplitude, and radial basis function is used as the kernel parameter which mapped the datasets into separable hyperplanes. The results showed 100% pattern recognition accuracy using SVM for both strain and micromotion. This indicates that DSP could be applied in determining the femoral stem primary stability with high pattern recognition accuracy in biomechanical testing.

  13. Primary Stability Recognition of the Newly Designed Cementless Femoral Stem Using Digital Signal Processing

    Science.gov (United States)

    Salleh, Sh-Hussain; Hamedi, Mahyar; Zulkifly, Ahmad Hafiz; Lee, Muhammad Hisyam; Mohd Noor, Alias; Harris, Arief Ruhullah A.; Abdul Majid, Norazman

    2014-01-01

    Stress shielding and micromotion are two major issues which determine the success of newly designed cementless femoral stems. The correlation of experimental validation with finite element analysis (FEA) is commonly used to evaluate the stress distribution and fixation stability of the stem within the femoral canal. This paper focused on the applications of feature extraction and pattern recognition using support vector machine (SVM) to determine the primary stability of the implant. We measured strain with triaxial rosette at the metaphyseal region and micromotion with linear variable direct transducer proximally and distally using composite femora. The root mean squares technique is used to feed the classifier which provides maximum likelihood estimation of amplitude, and radial basis function is used as the kernel parameter which mapped the datasets into separable hyperplanes. The results showed 100% pattern recognition accuracy using SVM for both strain and micromotion. This indicates that DSP could be applied in determining the femoral stem primary stability with high pattern recognition accuracy in biomechanical testing. PMID:24800230

  14. Primary stability recognition of the newly designed cementless femoral stem using digital signal processing.

    Science.gov (United States)

    Baharuddin, Mohd Yusof; Salleh, Sh-Hussain; Hamedi, Mahyar; Zulkifly, Ahmad Hafiz; Lee, Muhammad Hisyam; Mohd Noor, Alias; Harris, Arief Ruhullah A; Abdul Majid, Norazman

    2014-01-01

    Stress shielding and micromotion are two major issues which determine the success of newly designed cementless femoral stems. The correlation of experimental validation with finite element analysis (FEA) is commonly used to evaluate the stress distribution and fixation stability of the stem within the femoral canal. This paper focused on the applications of feature extraction and pattern recognition using support vector machine (SVM) to determine the primary stability of the implant. We measured strain with triaxial rosette at the metaphyseal region and micromotion with linear variable direct transducer proximally and distally using composite femora. The root mean squares technique is used to feed the classifier which provides maximum likelihood estimation of amplitude, and radial basis function is used as the kernel parameter which mapped the datasets into separable hyperplanes. The results showed 100% pattern recognition accuracy using SVM for both strain and micromotion. This indicates that DSP could be applied in determining the femoral stem primary stability with high pattern recognition accuracy in biomechanical testing.

  15. Applications of chaotic neurodynamics in pattern recognition

    Science.gov (United States)

    Baird, Bill; Freeman, Walter J.; Eeckman, Frank H.; Yao, Yong

    1991-08-01

    Network algorithms and architectures for pattern recognition derived from neural models of the olfactory system are reviewed. These span a range from highly abstract to physiologically detailed, and employ the kind of dynamical complexity observed in olfactory cortex, ranging from oscillation to chaos. A simple architecture and algorithm for analytically guaranteed associative memory storage of analog patterns, continuous sequences, and chaotic attractors in the same network is described. A matrix inversion determines network weights, given prototype patterns to be stored. There are N units of capacity in an N node network with 3N2 weights. It costs one unit per static attractor, two per Fourier component of each sequence, and three to four per chaotic attractor. There are no spurious attractors, and for sequences there is a Liapunov function in a special coordinate system which governs the approach of transient states to stored trajectories. Unsupervised or supervised incremental learning algorithms for pattern classification, such as competitive learning or bootstrap Widrow-Hoff can easily be implemented. The architecture can be ''folded'' into a recurrent network with higher order weights that can be used as a model of cortex that stores oscillatory and chaotic attractors by a Hebb rule. Network performance is demonstrated by application to the problem of real-time handwritten digit recognition. An effective system with on-line learning has been written by Eeckman and Baird for the Macintosh. It utilizes static, oscillatory, and/or chaotic attractors of two kinds--Lorenze attractors, or attractors resulting from chaotically interacting oscillatory modes. The successful application to an industrial pattern recognition problem of a network architecture of considerable physiological and dynamical complexity, developed by Freeman and Yao, is described. The data sets of the problem come in three classes of difficulty, and performance of the biological network is

  16. Modeling the lexical morphology of Western handwritten signatures.

    Directory of Open Access Journals (Sweden)

    Moises Diaz-Cabrera

    Full Text Available A handwritten signature is the final response to a complex cognitive and neuromuscular process which is the result of the learning process. Because of the many factors involved in signing, it is possible to study the signature from many points of view: graphologists, forensic experts, neurologists and computer vision experts have all examined them. Researchers study written signatures for psychiatric, penal, health and automatic verification purposes. As a potentially useful, multi-purpose study, this paper is focused on the lexical morphology of handwritten signatures. This we understand to mean the identification, analysis, and description of the signature structures of a given signer. In this work we analyze different public datasets involving 1533 signers from different Western geographical areas. Some relevant characteristics of signature lexical morphology have been selected, examined in terms of their probability distribution functions and modeled through a General Extreme Value distribution. This study suggests some useful models for multi-disciplinary sciences which depend on handwriting signatures.

  17. Identifying errors in handwritten outpatient prescriptions in oman.

    Science.gov (United States)

    Al Shahaibi, Nadiya Ms; Al Said, Lamya S; Kini, Tg; Chitme, Hr

    2012-10-01

    To evaluate and analyze the handwritten outpatient prescriptions and associated error of omissions from four different hospitals in Oman. The study designed was an observational, retrospective and analysis of prescriptions was carried out by table and chart method. A total of 900 prescriptions were collected between April 2009 to July 2010. The type of error of omissions considered in this analysis includes all three important parts of prescriptions, i.e. superscription, inscription, and subscription. The most common type of superscription error of omission was found to be age (72.44%) and gender (32.66%). More than 46% of prescriptions were incomplete on direction for use, more than 22% of prescriptions were not having the information on dose, and more than 23% of prescriptions omitted the dosage forms of prescribed drugs. The date of dispensing of medications was omitted in all the prescriptions and more than 44% of prescriptions were missing the signature of dispenser. It was also found that more than 4% of prescriptions omitted the prescriber's signature and more than 18% of prescriptions omitted the date of prescription. We conclude from this study that the handwritten prescriptions were associated with significant frequency of minor and major prescription error of omissions.

  18. Kernel-aligned multi-view canonical correlation analysis for image recognition

    Science.gov (United States)

    Su, Shuzhi; Ge, Hongwei; Yuan, Yun-Hao

    2016-09-01

    Existing kernel-based correlation analysis methods mainly adopt a single kernel in each view. However, only a single kernel is usually insufficient to characterize nonlinear distribution information of a view. To solve the problem, we transform each original feature vector into a 2-dimensional feature matrix by means of kernel alignment, and then propose a novel kernel-aligned multi-view canonical correlation analysis (KAMCCA) method on the basis of the feature matrices. Our proposed method can simultaneously employ multiple kernels to better capture the nonlinear distribution information of each view, so that correlation features learned by KAMCCA can have well discriminating power in real-world image recognition. Extensive experiments are designed on five real-world image datasets, including NIR face images, thermal face images, visible face images, handwritten digit images, and object images. Promising experimental results on the datasets have manifested the effectiveness of our proposed method.

  19. Assessing the impact of graphical quality on automatic text recognition in digital maps

    Science.gov (United States)

    Chiang, Yao-Yi; Leyk, Stefan; Honarvar Nazari, Narges; Moghaddam, Sima; Tan, Tian Xiang

    2016-08-01

    Converting geographic features (e.g., place names) in map images into a vector format is the first step for incorporating cartographic information into a geographic information system (GIS). With the advancement in computational power and algorithm design, map processing systems have been considerably improved over the last decade. However, the fundamental map processing techniques such as color image segmentation, (map) layer separation, and object recognition are sensitive to minor variations in graphical properties of the input image (e.g., scanning resolution). As a result, most map processing results would not meet user expectations if the user does not "properly" scan the map of interest, pre-process the map image (e.g., using compression or not), and train the processing system, accordingly. These issues could slow down the further advancement of map processing techniques as such unsuccessful attempts create a discouraged user community, and less sophisticated tools would be perceived as more viable solutions. Thus, it is important to understand what kinds of maps are suitable for automatic map processing and what types of results and process-related errors can be expected. In this paper, we shed light on these questions by using a typical map processing task, text recognition, to discuss a number of map instances that vary in suitability for automatic processing. We also present an extensive experiment on a diverse set of scanned historical maps to provide measures of baseline performance of a standard text recognition tool under varying map conditions (graphical quality) and text representations (that can vary even within the same map sheet). Our experimental results help the user understand what to expect when a fully or semi-automatic map processing system is used to process a scanned map with certain (varying) graphical properties and complexities in map content.

  20. Sign Language Recognition System using Neural Network for Digital Hardware Implementation

    Energy Technology Data Exchange (ETDEWEB)

    Vargas, Lorena P [Lorena Vargas Quintero, Optic and Computer Science Group - Universidad Popular del Cesar (Colombia); Barba, Leiner; Torres, C O; Mattos, L, E-mail: vargas.lorena@yahoo.com [Optic and Computer Science Group - Popular of Cesar University, Km 12, Valledupar (Colombia)

    2011-01-01

    This work presents an image pattern recognition system using neural network for the identification of sign language to deaf people. The system has several stored image that show the specific symbol in this kind of language, which is employed to teach a multilayer neural network using a back propagation algorithm. Initially, the images are processed to adapt them and to improve the performance of discriminating of the network, including in this process of filtering, reduction and elimination noise algorithms as well as edge detection. The system is evaluated using the signs without including movement in their representation.

  1. An Earthquake Recognition Algorithm Based on First-Digit Anomaly Entropy

    Science.gov (United States)

    Toledo, P. A.; Campos, J. A.

    2016-12-01

    The seismic signal identification problem is faced, under an environment ofsuperimposed events, through a detection algorithm based on statisticalpatterns, linked to Shannon entropy, obtained from the first-digit anomalypresent in seismograms. This new method exploits an information-invariantcontained in seismic signals, which is independent from the size of events, atleast in the range accessible to our observations. Algorithm performance iscompared versus a generic STA/LTA method using near field data from 11/3 2010Pichilemu Seismic Sequence. We show that both algorithms are complementary and itssimultaneous use increases the efficiency of detection.

  2. Recognition Of Powdery Mildew Disease For Betelvine Plants Using Digital Image Processing

    OpenAIRE

    Vijayakumar, J; Arumugam, S.

    2012-01-01

    The fresh leaves of betel vine are generally known as paan in India, which are inspired by about 20 – 30 million people in the country. It is cultivated in India about 75,000 hectares with an annual production worth about Rs. 1000 millions. Betelvine plants may have various disease infected in the entire plantation without any early indications of the diseases. The aim of this paper is to recognize powdery mildew disease in the betelvine plants using digital image processing and pattern reco...

  3. Digital Imprinting of RNA Recognition and Processing on a Self-Assembled Nucleic Acid Matrix

    Science.gov (United States)

    Redhu, Shiv K.; Castronovo, Matteo; Nicholson, Allen W.

    2013-08-01

    The accelerating progress of research in nanomedicine and nanobiotechnology has included initiatives to develop highly-sensitive, high-throughput methods to detect biomarkers at the single-cell level. Current sensing approaches, however, typically involve integrative instrumentation that necessarily must balance sensitivity with rapidity in optimizing biomarker detection quality. We show here that laterally-confined, self-assembled monolayers of a short, double-stranded(ds)[RNA-DNA] chimera enable permanent digital detection of dsRNA-specific inputs. The action of ribonuclease III and the binding of an inactive, dsRNA-binding mutant can be permanently recorded by the input-responsive action of a restriction endonuclease that cleaves an ancillary reporter site within the dsDNA segment. The resulting irreversible height change of the arrayed ds[RNA-DNA], as measured by atomic force microscopy, provides a distinct digital output for each dsRNA-specific input. These findings provide the basis for developing imprinting-based bio-nanosensors, and reveal the versatility of AFM as a tool for characterizing the behaviour of highly-crowded biomolecules at the nanoscale.

  4. Unsupervised Word Spotting in Historical Handwritten Document Images using Document-oriented Local Features.

    Science.gov (United States)

    Zagoris, Konstantinos; Pratikakis, Ioannis; Gatos, Basilis

    2017-05-03

    Word spotting strategies employed in historical handwritten documents face many challenges due to variation in the writing style and intense degradation. In this paper, a new method that permits effective word spotting in handwritten documents is presented that it relies upon document-oriented local features which take into account information around representative keypoints as well a matching process that incorporates spatial context in a local proximity search without using any training data. Experimental results on four historical handwritten datasets for two different scenarios (segmentation-based and segmentation-free) using standard evaluation measures show the improved performance achieved by the proposed methodology.

  5. Ancient administrative handwritten documents: X-ray analysis and imaging

    Energy Technology Data Exchange (ETDEWEB)

    Albertin, F., E-mail: fauzia.albertin@epfl.ch [Ecole Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne (Switzerland); Astolfo, A. [Paul Scherrer Institut (PSI), Villigen (Switzerland); Stampanoni, M. [Paul Scherrer Institut (PSI), Villigen (Switzerland); ETHZ, Zürich (Switzerland); Peccenini, Eva [University of Ferrara (Italy); Technopole of Ferrara (Italy); Hwu, Y. [Academia Sinica, Taipei, Taiwan (China); Kaplan, F. [Ecole Polytechnique Fédérale de Lausanne (EPFL) (Switzerland); Margaritondo, G. [Ecole Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne (Switzerland)

    2015-01-30

    The heavy-element content of ink in ancient administrative documents makes it possible to detect the characters with different synchrotron imaging techniques, based on attenuation or refraction. This is the first step in the direction of non-interactive virtual X-ray reading. Handwritten characters in administrative antique documents from three centuries have been detected using different synchrotron X-ray imaging techniques. Heavy elements in ancient inks, present even for everyday administrative manuscripts as shown by X-ray fluorescence spectra, produce attenuation contrast. In most cases the image quality is good enough for tomography reconstruction in view of future applications to virtual page-by-page ‘reading’. When attenuation is too low, differential phase contrast imaging can reveal the characters from refractive index effects. The results are potentially important for new information harvesting strategies, for example from the huge Archivio di Stato collection, objective of the Venice Time Machine project.

  6. Recognition of tennis serve performed by a digital player: comparison among polygon, shadow, and stick-figure models.

    Directory of Open Access Journals (Sweden)

    Hirofumi Ida

    Full Text Available The objective of this study was to assess the cognitive effect of human character models on the observer's ability to extract relevant information from computer graphics animation of tennis serve motions. Three digital human models (polygon, shadow, and stick-figure were used to display the computationally simulated serve motions, which were perturbed at the racket-arm by modulating the speed (slower or faster of one of the joint rotations (wrist, elbow, or shoulder. Twenty-one experienced tennis players and 21 novices made discrimination responses about the modulated joint and also specified the perceived swing speeds on a visual analogue scale. The result showed that the discrimination accuracies of the experienced players were both above and below chance level depending on the modulated joint whereas those of the novices mostly remained at chance or guessing levels. As far as the experienced players were concerned, the polygon model decreased the discrimination accuracy as compared with the stick-figure model. This suggests that the complicated pictorial information may have a distracting effect on the recognition of the observed action. On the other hand, the perceived swing speed of the perturbed motion relative to the control was lower for the stick-figure model than for the polygon model regardless of the skill level. This result suggests that the simplified visual information can bias the perception of the motion speed toward slower. It was also shown that the increasing the joint rotation speed increased the perceived swing speed, although the resulting racket velocity had little correlation with this speed sensation. Collectively, observer's recognition of the motion pattern and perception of the motion speed can be affected by the pictorial information of the human model as well as by the perturbation processing applied to the observed motion.

  7. Recognition of tennis serve performed by a digital player: comparison among polygon, shadow, and stick-figure models.

    Science.gov (United States)

    Ida, Hirofumi; Fukuhara, Kazunobu; Ishii, Motonobu

    2012-01-01

    The objective of this study was to assess the cognitive effect of human character models on the observer's ability to extract relevant information from computer graphics animation of tennis serve motions. Three digital human models (polygon, shadow, and stick-figure) were used to display the computationally simulated serve motions, which were perturbed at the racket-arm by modulating the speed (slower or faster) of one of the joint rotations (wrist, elbow, or shoulder). Twenty-one experienced tennis players and 21 novices made discrimination responses about the modulated joint and also specified the perceived swing speeds on a visual analogue scale. The result showed that the discrimination accuracies of the experienced players were both above and below chance level depending on the modulated joint whereas those of the novices mostly remained at chance or guessing levels. As far as the experienced players were concerned, the polygon model decreased the discrimination accuracy as compared with the stick-figure model. This suggests that the complicated pictorial information may have a distracting effect on the recognition of the observed action. On the other hand, the perceived swing speed of the perturbed motion relative to the control was lower for the stick-figure model than for the polygon model regardless of the skill level. This result suggests that the simplified visual information can bias the perception of the motion speed toward slower. It was also shown that the increasing the joint rotation speed increased the perceived swing speed, although the resulting racket velocity had little correlation with this speed sensation. Collectively, observer's recognition of the motion pattern and perception of the motion speed can be affected by the pictorial information of the human model as well as by the perturbation processing applied to the observed motion.

  8. Verification of the authenticity of handwritten signature using structure neural-network-type OCON

    Science.gov (United States)

    Molina, M. L.; Arias, N. A.; Gualdron, Oscar

    2004-10-01

    A method in order to carry out the verification of handwritten signatures is described. The method keeps in mind global features and local features that encode the shape and the dynamics of the signatures. Signatures are recorded with a digital tablet that can read the position and pressure of the pen. Input patterns are considered time and space dependent. Before extracting the information of the static features such as total length or height/width ratio, and the dynamic features such as speed or acceleration, the signature is normalized for position, size and orientation using its Fourier Descriptors. The comparison stage is carried out for algorithms of neurals networks. For each one of the sets of features a special two stage Perceptron OCON (one-class-one-network) classification structure has been implemented. In the first stage networks multilayer perceptron with few neurons are used. The classifier combines the decision results of the neural networks and the Euclidean distance obtained using the two feature sets. The results of the first-stage classifier feed a second-stage radial basis function (RBF) neural network structure, which makes the final decision. The entire system was extensively tested, 160 neurals networks has been implemented.

  9. Analogies Between Digital Radio and Chemical Orthogonality as a Method for Enhanced Analysis of Molecular Recognition Events

    Directory of Open Access Journals (Sweden)

    Sang-Hun Lee

    2008-02-01

    Full Text Available Acoustic wave biosensors are a real-time, label-free biosensor technology, which have been exploited for the detection of proteins and cells. One of the conventional biosensor approaches involves the immobilization of a monolayer of antibodies onto the surface of the acoustic wave device for the detection of a specific analyte. The method described within includes at least two immobilizations of two different antibodies onto the surfaces of two separate acoustic wave devices for the detection of several analogous analytes. The chemical specificity of the molecular recognition event is achieved by virtue of the extremely high (nM to pM binding affinity between the antibody and its antigen. In a standard ELISA (Enzyme-Linked ImmunoSorbent Assay test, there are multiple steps and the end result is a measure of what is bound so tightly that it does not wash away easily. The fact that this “gold standard” is very much not real time, masks the dance that is the molecular recognition event. X-Ray Crystallographer, Ian Wilson, demonstrated more than a decade ago that antibodies undergo conformational change during a binding event[1, 2]. Further, it is known in the arena of immunochemistry that some antibodies exhibit significant cross-reactivity and this is widely termed antibody promiscuity. A third piece of the puzzle that we will exploit in our system of acoustic wave biosensors is the notion of chemical orthogonality. These three biochemical constructs, the dance, antibody promiscuity and chemical orthogonality will be combined in this paper with the notions of Int. J. Mol. Sci. 2008, 9 155 in-phase (I and quadrature (Q signals from digital radio to manifest an approach to molecular recognition that allows a level of discrimination and analysis unobtainable without the aggregate. As an example we present experimental data on the detection of TNT, RDX, C4, ammonium nitrate and musk oil from a system of antibody-coated acoustic

  10. Extracting contextual information in digital imagery: applications to automatic target recognition and mammography

    Science.gov (United States)

    Spence, Clay D.; Sajda, Paul; Pearson, John C.

    1996-02-01

    An important problem in image analysis is finding small objects in large images. The problem is challenging because (1) searching a large image is computationally expensive, and (2) small targets (on the order of a few pixels in size) have relatively few distinctive features which enable them to be distinguished from non-targets. To overcome these challenges we have developed a hierarchical neural network (HNN) architecture which combines multi-resolution pyramid processing with neural networks. The advantages of the architecture are: (1) both neural network training and testing can be done efficiently through coarse-to-fine techniques, and (2) such a system is capable of learning low-resolution contextual information to facilitate the detection of small target objects. We have applied this neural network architecture to two problems in which contextual information appears to be important for detecting small targets. The first problem is one of automatic target recognition (ATR), specifically the problem of detecting buildings in aerial photographs. The second problem focuses on a medical application, namely searching mammograms for microcalcifications, which are cues for breast cancer. Receiver operating characteristic (ROC) analysis suggests that the hierarchical architecture improves the detection accuracy for both the ATR and microcalcification detection problems, reducing false positive rates by a significant factor. In addition, we have examined the hidden units at various levels of the processing hierarchy and found what appears to be representations of road location (for the ATR example) and ductal/vasculature location (for mammography), both of which are in agreement with the contextual information used by humans to find these classes of targets. We conclude that this hierarchical neural network architecture is able to automatically extract contextual information in imagery and utilize it for target detection.

  11. Statistical pattern recognition for automatic writer identification and verification

    NARCIS (Netherlands)

    Bulacu, Marius Lucian

    2007-01-01

    The thesis addresses the problem of automatic person identification using scanned images of handwriting.Identifying the author of a handwritten sample using automatic image-based methods is an interesting pattern recognition problem with direct applicability in the forensic and historic document

  12. Digitization

    DEFF Research Database (Denmark)

    Finnemann, Niels Ole

    2014-01-01

    Processes of digitization have for years represented a major trend in the developments of modern society but have only recently been related to processes of mediatization. The purpose of this article is to look into the relation between the concepts of mediatization and digitization and to clarify...... what a concept of digital media might add to the understanding of processes of mediatization and what the concept of mediatization might add to the understanding of digital media. It is argued that digital media open an array of new trajectories in human communication, trajectories which were...... not anticipated in previous conceptualizations of media and mediatization. If digital media are to be included, the concept of mediatization has to be revised and new parameters are to be built into the concept of media. At the same time it is argued that the concept of mediatization still provides a variety...

  13. 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.

  14. Off-line cursive handwriting recognition using multiple classifier systems—on the influence of vocabulary, ensemble, and training set size

    Science.gov (United States)

    Günter, Simon; Bunke, Horst

    2005-03-01

    Unconstrained handwritten text recognition is one of the most difficult problems in the field of pattern recognition. Recently, a number of classifier creation and combination methods, known as ensemble methods, have been proposed in the field of machine learning. They have shown improved recognition performance over single classifiers. In this paper, we examine the influence of the vocabulary size, the number of training samples, and the number of classifiers on the performance of three ensemble methods in the context of cursive handwriting recognition. All experiments were conducted using an off-line handwritten word recognizer based on hidden Markov models (HMMs).

  15. Variational dynamic background model for keyword spotting in handwritten documents

    Science.gov (United States)

    Kumar, Gaurav; Wshah, Safwan; Govindaraju, Venu

    2013-12-01

    We propose a bayesian framework for keyword spotting in handwritten documents. This work is an extension to our previous work where we proposed dynamic background model, DBM for keyword spotting that takes into account the local character level scores and global word level scores to learn a logistic regression classifier to separate keywords from non-keywords. In this work, we add a bayesian layer on top of the DBM called the variational dynamic background model, VDBM. The logistic regression classifier uses the sigmoid function to separate keywords from non-keywords. The sigmoid function being neither convex nor concave, exact inference of VDBM becomes intractable. An expectation maximization step is proposed to do approximate inference. The advantage of VDBM over the DBM is multi-fold. Firstly, being bayesian, it prevents over-fitting of data. Secondly, it provides better modeling of data and an improved prediction of unseen data. VDBM is evaluated on the IAM dataset and the results prove that it outperforms our prior work and other state of the art line based word spotting system.

  16. Achieving high recognition reliability using decision trees and AdaBoost

    Science.gov (United States)

    Xiang, Jianying; Tu, Xiao; Lu, Yue; Wang, Patrick S. P.

    2008-01-01

    Recognition rate is traditionally used as the main criterion for evaluating the performance of a recognition system. High recognition reliability with low misclassification rate is also a must for many applications. To handle the variability of the writing style of different individuals, this paper employs decision trees and WRB AdaBoost to design a classifier with high recognition reliability for recognizing Bangla handwritten numerals. Experiments on the numeral images obtained from real Bangladesh envelopes show that the proposed recognition method is capable of achieving high recognition reliability with acceptable recognition rate.

  17. Influence of the signer's psychophysiological state on the results of his identification using handwritten pattern by natural and artificial intelligence

    Directory of Open Access Journals (Sweden)

    Alexey E. Sulavko

    2017-11-01

    Full Text Available At present, while various mechanisms to ensure information security are actively being improved, particular attention is paid to prevent unauthorized access to information resources.  The human factor and process of identification still remain the most problematic, as well as user authentication. A progress in the technology of information resources protection from internal security threats paves its way towards biometric systems of hidden identification of computer users and their psychophysiological state. A change in psychophysiological state results in the person's handwriting. The influence of the signer’s state of fatigue and excitation on the results of its identification both by a person and by pattern recognition methods on reproduced signatures are studied. Capabilities of human and artificial intelligence are compared in equal conditions. When the state of the signer changes, the probability of erroneous recognition by artificial intelligence increases by factor 3.3 to 3.7. A person identifies a handwritten image with fewer errors in case when the signer is agitated, and with higher error rate if the signer is tired.

  18. Hybrid evolutionary techniques in feed forward neural network with distributed error for classification of handwritten Hindi `SWARS'

    Science.gov (United States)

    Kumar, Somesh; Pratap Singh, Manu; Goel, Rajkumar; Lavania, Rajesh

    2013-12-01

    In this work, the performance of feedforward neural network with a descent gradient of distributed error and the genetic algorithm (GA) is evaluated for the recognition of handwritten 'SWARS' of Hindi curve script. The performance index for the feedforward multilayer neural networks is considered here with distributed instantaneous unknown error i.e. different error for different layers. The objective of the GA is to make the search process more efficient to determine the optimal weight vectors from the population. The GA is applied with the distributed error. The fitness function of the GA is considered as the mean of square distributed error that is different for each layer. Hence the convergence is obtained only when the minimum of different errors is determined. It has been analysed that the proposed method of a descent gradient of distributed error with the GA known as hybrid distributed evolutionary technique for the multilayer feed forward neural performs better in terms of accuracy, epochs and the number of optimal solutions for the given training and test pattern sets of the pattern recognition problem.

  19. Handwritten Character Classification using the Hotspot Feature Extraction Technique

    NARCIS (Netherlands)

    Surinta, Olarik; Schomaker, Lambertus; Wiering, Marco

    2012-01-01

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

  20. THE SEGMENTATION OF A TEXT LINE FOR A HANDWRITTEN UNCONSTRAINED DOCUMENT USING THINING ALGORITHM

    NARCIS (Netherlands)

    Tsuruoka, S.; Adachi, Y.; Yoshikawa, T.

    2004-01-01

    For printed documents, the projection analysis of black pixels is widely used for the segmentation of a text line. However, for handwritten documents, we think that the projection analysis is not appropriate, as the separating border line of a text line is not a straight line on a paper with no

  1. Junction detection in handwritten documents and its application to writer identification

    NARCIS (Netherlands)

    He, Sheng; Wiering, Marco; Schomaker, Lambert

    2015-01-01

    In this paper, we propose a novel junction detection method in handwritten images, which uses the stroke-length distribution in every direction around a reference point inside the ink of texts. Our proposed junction detection method is simple and efficient, and yields a junction feature in a natural

  2. AN APPROACH FOR ACTIVE SEGMENTATION OF UNCONSTRAINED HANDWRITTEN KOREAN STRINGS USING RUN-LENGTH CODE

    NARCIS (Netherlands)

    JeongSuk, J.; Kim, G.

    2004-01-01

    We propose an active handwritten Hangul segmentation method. A manageable structure based on Run-length code is defined in order to apply to preprocessing and segmentation. Also three fundamental candidate estimation functions are in- troduced to detect the clues on touching points, and the

  3. Recognition of tennis serve performed by a digital player: comparison among polygon, shadow, and stick-figure models

    National Research Council Canada - National Science Library

    Ida, Hirofumi; Fukuhara, Kazunobu; Ishii, Motonobu

    2012-01-01

    .... Three digital human models (polygon, shadow, and stick-figure) were used to display the computationally simulated serve motions, which were perturbed at the racket-arm by modulating the speed (slower or faster...

  4. A comparative study between MFCC and LSF coefficients in automatic recognition of isolated digits pronounced in Portuguese and English - doi: 10.4025/actascitechnol.v35i4.19825

    Directory of Open Access Journals (Sweden)

    Diego Furtado Silva

    2013-10-01

    Full Text Available Recognition of isolated spoken digits is the core procedure for a large number of applications which rely solely on speech for data exchange, as in telephone-based services, such as dialing, airline reservation, bank transaction and price quotation. Spoken digit recognition is generally a challenging task since the signals last for a short period of time and often some digits are acoustically very similar to other digits. The objective of this paper is to investigate the use of machine learning algorithms for spoken digit recognition and disclose the free availability of a database with digits pronounced in English and Portuguese to the scientific community. Since machine learning algorithms are fully dependent on predictive attributes to build precise classifiers, we believe that the most important task for successfully recognizing spoken digits is feature extraction. In this work, we show that Line Spectral Frequencies (LSF provide a set of highly predictive coefficients. We evaluated our classifiers in different settings by altering the sampling rate to simulate low quality channels and varying the number of coefficients.  

  5. Adaptive spatial filtering for off-axis digital holographic microscopy based on region recognition approach with iterative thresholding

    Science.gov (United States)

    He, Xuefei; Nguyen, Chuong Vinh; Pratap, Mrinalini; Zheng, Yujie; Wang, Yi; Nisbet, David R.; Rug, Melanie; Maier, Alexander G.; Lee, Woei Ming

    2016-12-01

    Here we propose a region-recognition approach with iterative thresholding, which is adaptively tailored to extract the appropriate region or shape of spatial frequency. In order to justify the method, we tested it with different samples and imaging conditions (different objectives). We demonstrate that our method provides a useful method for rapid imaging of cellular dynamics in microfluidic and cell cultures.

  6. A model-based sequence similarity with application to handwritten word spotting.

    Science.gov (United States)

    Rodríguez-Serrano, José A; Perronnin, Florent

    2012-11-01

    This paper proposes a novel similarity measure between vector sequences. We work in the framework of model-based approaches, where each sequence is first mapped to a Hidden Markov Model (HMM) and then a measure of similarity is computed between the HMMs. We propose to model sequences with semicontinuous HMMs (SC-HMMs). This is a particular type of HMM whose emission probabilities in each state are mixtures of shared Gaussians. This crucial constraint provides two major benefits. First, the a priori information contained in the common set of Gaussians leads to a more accurate estimate of the HMM parameters. Second, the computation of a similarity between two SC-HMMs can be simplified to a Dynamic Time Warping (DTW) between their mixture weight vectors, which significantly reduces the computational cost. Experiments are carried out on a handwritten word retrieval task in three different datasets-an in-house dataset of real handwritten letters, the George Washington dataset, and the IFN/ENIT dataset of Arabic handwritten words. These experiments show that the proposed similarity outperforms the traditional DTW between the original sequences, and the model-based approach which uses ordinary continuous HMMs. We also show that this increase in accuracy can be traded against a significant reduction of the computational cost.

  7. Tuning Recurrent Neural Networks for Recognizing Handwritten Arabic Words

    KAUST Repository

    Qaralleh, Esam

    2013-10-01

    Artificial neural networks have the abilities to learn by example and are capable of solving problems that are hard to solve using ordinary rule-based programming. They have many design parameters that affect their performance such as the number and sizes of the hidden layers. Large sizes are slow and small sizes are generally not accurate. Tuning the neural network size is a hard task because the design space is often large and training is often a long process. We use design of experiments techniques to tune the recurrent neural network used in an Arabic handwriting recognition system. We show that best results are achieved with three hidden layers and two subsampling layers. To tune the sizes of these five layers, we use fractional factorial experiment design to limit the number of experiments to a feasible number. Moreover, we replicate the experiment configuration multiple times to overcome the randomness in the training process. The accuracy and time measurements are analyzed and modeled. The two models are then used to locate network sizes that are on the Pareto optimal frontier. The approach described in this paper reduces the label error from 26.2% to 19.8%.

  8. Development of a Digitalized Child's Checkups Information System.

    Science.gov (United States)

    Ito, Yoshiya; Takimoto, Hidemi

    2017-01-01

    In Japan, health checkups for children take place from infancy through high school and play an important role in the maintenance and control of childhood/adolescent health. The anthropometric data obtained during these checkups are kept in health centers and schools and are also recorded in a mother's maternal and child health handbook, as well as on school health cards. These data are meaningful if they are utilized well and in an appropriate manner. They are particularly useful for the prevention of obesity-related conditions in adulthood, such as metabolic syndrome and diabetes mellitus. For this purpose, we have tried to establish a scanning system with an optical character recognition (OCR) function, which links data obtained during health checkups in infancy with that obtained in schools. In this system, handwritten characters on the records are scanned and processed using OCR. However, because many of the scanned characters are not read properly, we must wait for the improvement in the performance of the OCR function. In addition, we have developed Microsoft Excel spreadsheets, on which obesity-related indices, such as body mass index and relative body weight, are calculated. These sheets also provide functions that tabulate the frequencies of obesity in specific groups. Actively using these data and digitalized systems will not only contribute towards resolving physical health problems in children, but also decrease the risk of developing lifestyle-related diseases in adulthood.

  9. Recognition of handwriting from electromyography.

    Directory of Open Access Journals (Sweden)

    Michael Linderman

    Full Text Available 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.

  10. Recognition of handwriting from electromyography.

    Science.gov (United States)

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

    2009-08-26

    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.

  11. Human red blood cell recognition enhancement with three-dimensional morphological features obtained by digital holographic imaging

    Science.gov (United States)

    Jaferzadeh, Keyvan; Moon, Inkyu

    2016-12-01

    The classification of erythrocytes plays an important role in the field of hematological diagnosis, specifically blood disorders. Since the biconcave shape of red blood cell (RBC) is altered during the different stages of hematological disorders, we believe that the three-dimensional (3-D) morphological features of erythrocyte provide better classification results than conventional two-dimensional (2-D) features. Therefore, we introduce a set of 3-D features related to the morphological and chemical properties of RBC profile and try to evaluate the discrimination power of these features against 2-D features with a neural network classifier. The 3-D features include erythrocyte surface area, volume, average cell thickness, sphericity index, sphericity coefficient and functionality factor, MCH and MCHSD, and two newly introduced features extracted from the ring section of RBC at the single-cell level. In contrast, the 2-D features are RBC projected surface area, perimeter, radius, elongation, and projected surface area to perimeter ratio. All features are obtained from images visualized by off-axis digital holographic microscopy with a numerical reconstruction algorithm, and four categories of biconcave (doughnut shape), flat-disc, stomatocyte, and echinospherocyte RBCs are interested. Our experimental results demonstrate that the 3-D features can be more useful in RBC classification than the 2-D features. Finally, we choose the best feature set of the 2-D and 3-D features by sequential forward feature selection technique, which yields better discrimination results. We believe that the final feature set evaluated with a neural network classification strategy can improve the RBC classification accuracy.

  12. 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.

  13. The Comparison of Typed and Handwritten Essays of Iranian EFL Students in terms of Length, Spelling, and Grammar

    Directory of Open Access Journals (Sweden)

    Behrouz Sarbakhshian

    2016-11-01

    Full Text Available This study attempted to compare typed and handwritten essays of Iranian EFL students in terms of length, spelling, and grammar. To administer the study, the researchers utilized Alice Touch Typing Tutor software to select 15 upper intermediate students with higher ability to write two essays: one typed and the other handwritten. The students were both males and females between the ages of 22 to 35. The analyses of the students’ scores in the three mentioned criteria through three paired samples t-tests indicate that typed essays are significantly better than handwritten ones in terms of length of texts and grammatical mistakes, but not significantly different in spelling mistakes. Positive effects of typing can provide a logical reason for students, especially TOEFL applicants, to spend more time on acquiring typing skill and also for teachers to encourage their students with higher typing ability to choose typed format in their essays.

  14. Corticospinal excitability during the processing of handwritten and typed words and non-words.

    Science.gov (United States)

    Gordon, Chelsea L; Spivey, Michael J; Balasubramaniam, Ramesh

    2017-06-09

    A number of studies have suggested that perception of actions is accompanied by motor simulation of those actions. To further explore this proposal, we applied Transcranial magnetic stimulation (TMS) to the left primary motor cortex during the observation of handwritten and typed language stimuli, including words and non-word consonant clusters. We recorded motor-evoked potentials (MEPs) from the right first dorsal interosseous (FDI) muscle to measure cortico-spinal excitability during written text perception. We observed a facilitation in MEPs for handwritten stimuli, regardless of whether the stimuli were words or non-words, suggesting potential motor simulation during observation. We did not observe a similar facilitation for the typed stimuli, suggesting that motor simulation was not occurring during observation of typed text. By demonstrating potential simulation of written language text during observation, these findings add to a growing literature suggesting that the motor system plays a strong role in the perception of written language. Copyright © 2017 Elsevier B.V. All rights reserved.

  15. The use of discrete-event simulation modeling to compare handwritten and electronic prescribing systems.

    Science.gov (United States)

    Ghany, Ahmad; Vassanji, Karim; Kuziemsky, Craig; Keshavjee, Karim

    2013-01-01

    Electronic prescribing (e-prescribing) is expected to bring many benefits to Canadian healthcare, such as a reduction in errors and adverse drug reactions. As there currently is no functioning e-prescribing system in Canada that is completely electronic, we are unable to evaluate the performance of a live system. An alternative approach is to use simulation modeling for evaluation. We developed two discrete-event simulation models, one of the current handwritten prescribing system and one of a proposed e-prescribing system, to compare the performance of these two systems. We were able to compare the number of processes in each model, workflow efficiency, and the distribution of patients or prescriptions. Although we were able to compare these models to each other, using discrete-event simulation software was challenging. We were limited in the number of variables we could measure. We discovered non-linear processes and feedback loops in both models that could not be adequately represented using discrete-event simulation software. Finally, interactions between entities in both models could not be modeled using this type of software. We have come to the conclusion that a more appropriate approach to modeling both the handwritten and electronic prescribing systems would be to use a complex adaptive systems approach using agent-based modeling or systems-based modeling.

  16. Data quality associated with handwritten laboratory test requests: classification and frequency of data-entry errors for outpatient serology tests.

    Science.gov (United States)

    Vecellio, Elia; Malley, Michael W; Toouli, George; Georgiou, Andrew; Westbrook, Johanna I

    2015-01-01

    Manual data-entry of handwritten laboratory test requests into electronic information systems has implications for data accuracy. This study sought to identify the types and number of errors occurring for handwritten serology test requests received from outpatient clinics. A 15-day audit at a serology laboratory in Sydney, Australia, compared the content of all transcribed serology outpatient test requests in the laboratory information system with the handwritten request form. One or more errors were detected in 67/627 (10.7%) audited requests (N=68 errors). Fifty-one of the errors (75.0%) were transcription errors: the wrong test was transcribed in 40/68 cases (58.8%)--ten of these occurred when the abbreviations 'HBsAb' and 'HBsAg' were confounded for one another--and transcribed requests were missing a test in 11/68 cases (16.2%). The remaining 17 non-transcription errors (25.0%) described request forms not signed by the ordering clinician, mislabelled specimens, and wrong tests due to computer algorithm errors. Manual data-entry of handwritten serology requests is an error-prone process. Electronic ordering has the potential to eliminate illegible handwriting and transcription errors, thus improving data accuracy in hospital information systems.

  17. High incidence of medication documentation errors in a Swiss university hospital due to the handwritten prescription process

    Directory of Open Access Journals (Sweden)

    Röder Christoph

    2011-08-01

    Full Text Available Abstract Background Medication errors have been reported to be a leading cause of death in hospitalized patients. In this study we focused on identifying and quantifying errors in the handwritten drug ordering and dispensing documentation processes which could possibly lead to adverse drug events. Methods We studied 1,934 ordered agents (165 consecutive patients retrospectively for medication documentation errors. Errors were categorized into: Prescribing errors, transcription errors and administration documentation errors on the nurses' medication lists. The legibility of prescriptions was analyzed to explore its possible influence on the error rate in the documentation process. Results Documentation errors occurred in 65 of 1,934 prescribed agents (3.5%. The incidence of patient charts showing at least one error was 43%. Prescribing errors were found 39 times (37%, transcription errors 56 times (53%, and administration documentation errors 10 times (10%. The handwriting readability was rated as good in 2%, moderate in 42%, bad in 52%, and unreadable in 4%. Conclusions This study revealed a high incidence of documentation errors in the traditional handwritten prescription process. Most errors occurred when prescriptions were transcribed into the patients' chart. The readability of the handwritten prescriptions was generally bad. Replacing the traditional handwritten documentation process with information technology could potentially improve the safety in the medication process.

  18. Classification and Verification of Handwritten Signatures with Time Causal Information Theory Quantifiers.

    Science.gov (United States)

    Rosso, Osvaldo A; Ospina, Raydonal; Frery, Alejandro C

    2016-01-01

    We present a new approach for handwritten signature classification and verification based on descriptors stemming from time causal information theory. The proposal uses the Shannon entropy, the statistical complexity, and the Fisher information evaluated over the Bandt and Pompe symbolization of the horizontal and vertical coordinates of signatures. These six features are easy and fast to compute, and they are the input to an One-Class Support Vector Machine classifier. The results are better than state-of-the-art online techniques that employ higher-dimensional feature spaces which often require specialized software and hardware. We assess the consistency of our proposal with respect to the size of the training sample, and we also use it to classify the signatures into meaningful groups.

  19. Linguistic characterization of handwritten documents, century XVII in Santiago de Cuba

    Directory of Open Access Journals (Sweden)

    Irina Bidot-Martínez

    2017-01-01

    Full Text Available The work focuses on the description from the lexical-semantic-phonic chart and morphosyntactic levels of 40 handwritten documents (baptismal records and notarial protocols located in the provincial and Historical Archive of the Archbishopric of Santiago de Cuba, to contribute to the study of the history of the Cuban variant of the language. This work provides the linguistic description, the paleographic transcription and rescue of the documents under consideration and determination of its formulaic structure that responds generally to the scheme: dating, provision of the Act, references to the participants and signatures of witness. These results are inserted into the line “Documentary sources in eastern of Cuba and its contribution to the rescue, preservation and promotion of heritage” VLIR Project “Social, humanities and architecture: Facing the Challenges of Local Development in Santiago de Cuba. The Enhancement of Heritage Preservation”.

  20. Classification and Verification of Handwritten Signatures with Time Causal Information Theory Quantifiers.

    Directory of Open Access Journals (Sweden)

    Osvaldo A Rosso

    Full Text Available We present a new approach for handwritten signature classification and verification based on descriptors stemming from time causal information theory. The proposal uses the Shannon entropy, the statistical complexity, and the Fisher information evaluated over the Bandt and Pompe symbolization of the horizontal and vertical coordinates of signatures. These six features are easy and fast to compute, and they are the input to an One-Class Support Vector Machine classifier. The results are better than state-of-the-art online techniques that employ higher-dimensional feature spaces which often require specialized software and hardware. We assess the consistency of our proposal with respect to the size of the training sample, and we also use it to classify the signatures into meaningful groups.

  1. Using an Unmanned Aerial Vehicle-Based Digital Imaging System to Derive a 3D Point Cloud for Landslide Scarp Recognition

    Directory of Open Access Journals (Sweden)

    Abdulla Al-Rawabdeh

    2016-01-01

    Full Text Available Landslides often cause economic losses, property damage, and loss of lives. Monitoring landslides using high spatial and temporal resolution imagery and the ability to quickly identify landslide regions are the basis for emergency disaster management. This study presents a comprehensive system that uses unmanned aerial vehicles (UAVs and Semi-Global dense Matching (SGM techniques to identify and extract landslide scarp data. The selected study area is located along a major highway in a mountainous region in Jordan, and contains creeping landslides induced by heavy rainfall. Field observations across the slope body and a deformation analysis along the highway and existing gabions indicate that the slope is active and that scarp features across the slope will continue to open and develop new tension crack features, leading to the downward movement of rocks. The identification of landslide scarps in this study was performed via a dense 3D point cloud of topographic information generated from high-resolution images captured using a low-cost UAV and a target-based camera calibration procedure for a low-cost large-field-of-view camera. An automated approach was used to accurately detect and extract the landslide head scarps based on geomorphological factors: the ratio of normalized Eigenvalues (i.e., λ1/λ2 ≥ λ3 derived using principal component analysis, topographic surface roughness index values, and local-neighborhood slope measurements from the 3D image-based point cloud. Validation of the results was performed using root mean square error analysis and a confusion (error matrix between manually digitized landslide scarps and the automated approaches. The experimental results using the fully automated 3D point-based analysis algorithms show that these approaches can effectively distinguish landslide scarps. The proposed algorithms can accurately identify and extract landslide scarps with centimeter-scale accuracy. In addition, the combination

  2. Reconhecimento de variedades de soja por meio do processamento de imagens digitais usando redes neurais artificiais Soybean varieties recognition through the digital image processing using artificial neural network

    Directory of Open Access Journals (Sweden)

    Oleg Khatchatourian

    2008-12-01

    Full Text Available Neste trabalho, foi aplicado o processamento de imagens digitais auxiliado pelas Redes Neurais Artificiais (RNA com a finalidade de identificar algumas variedades de soja por meio da forma e do tamanho das sementes. Foram analisadas as seguintes variedades: EMBRAPA 133, EMBRAPA 184, COODETEC 205, COODETEC 206, EMBRAPA 48, SYNGENTA 8350, FEPAGRO 10 e MONSOY 8000 RR, safra 2005/2006. O processamento das imagens foi constituído pelas seguintes etapas: 1 Aquisição da imagem: as amostras de cada variedade foram fotografadas por máquina fotográfica Coolpix995, Nikon, com resolução de 3.34 megapixels; 2 Pré-processamento: um filtro de anti-aliasing foi aplicado para obter tons acinzentados da imagem; 3 Segmentação: foi realizada a detecção das bordas das sementes (Método de Prewitt, dilatação dessas bordas e remoção de segmentos não-necessários para a análise. 4 Representação: cada semente foi representada na forma de matriz binária 130x130, e 5 Reconhecimento e interpretação: foi utilizada uma rede neural feedforward multicamadas, com três camadas ocultas. O treinamento da rede foi realizado pelo método backpropagation. A validação da RNA treinada mostrou que o processamento aplicado pode ser usado para a identificação das variedades consideradas.Digital image processing with Artificial Neural Network (ANN was used to identify some soybean varieties through the form and size of the seeds. The following varieties were analyzed: EMBRAPA 133, EMBRAPA 184, COODETEC 205, COODETEC 206, EMBRAPA 48, SYNGENTA 8350, FEPAGRO 10 and MONSOY 8000 RR, 2005/2006 harvest. The image processing was constituted by the following stages: 1 Image acquisition: the samples of each variety were photographed by photographic camera Coolpix995, Nikon, with resolution of 3.34 megapixels; 2 Pre-processing: an anti-aliasing filter was applied to convert the true-color image to the grayscale intensity image; 3 Segmentation: it was made the seeds edges

  3. Multi-agent Systems for Arabic Handwriting Recognition

    Directory of Open Access Journals (Sweden)

    Youssef Boulid

    2017-12-01

    Full Text Available This paper aims to give a presentation of the PhD defended by Boulid Youssef on December 26th, 2016 at University Ibn Tofail, entitled “Arabic handwritten recognition in an offline mode”. The adopted approach is realized under the multi agent paradigm. The dissertation was held in Faculty of Science Kénitra in a publicly open presentation. After the presentation, Boulid was awarded with the highest grade (Très honorable avec félicitations de jury.

  4. Fusion of statistical and structural information for flowchart recognition

    OpenAIRE

    Carton, Cérès; Lemaitre, Aurélie; Couasnon, Bertrand

    2013-01-01

    International audience; A critical step of on-line handwritten diagram recognition is the segmentation between text and symbols. It is still an open problem in several approaches of the literature. However, for a human operator, text/symbol segmentation is an easy task and does not even need understanding diagram semantics. It is done thanks to the use of both structural knowledge and statistical analysis. A human operator knows what is a symbol and how to distinguish a good symbol from a bad...

  5. Writer adaptation in off-line Arabic handwriting recognition

    Science.gov (United States)

    Ball, Gregory R.; Srihari, Sargur N.

    2008-01-01

    Writer adaptation or specialization is the adjustment of handwriting recognition algorithms to a specific writer's style of handwriting. Such adjustment yields significantly improved recognition rates over counterpart general recognition algorithms. We present the first unconstrained off-line handwriting adaptation algorithm for Arabic presented in the literature. We discuss an iterative bootstrapping model which adapts a writer-independent model to a writer-dependent model using a small number of words achieving a large recognition rate increase in the process. Furthermore, we describe a confidence weighting method which generates better results by weighting words based on their length. We also discuss script features unique to Arabic, and how we incorporate them into our adaptation process. Even though Arabic has many more character classes than languages such as English, significant improvement was observed. The testing set consisting of about 100 pages of handwritten text had an initial average overall recognition rate of 67%. After the basic adaptation was finished, the overall recognition rate was 73.3%. As the improvement was most marked for the longer words, and the set of confidently recognized longer words contained many fewer false results, a second method was presented using them alone, resulting in a recognition rate of about 75%. Initially, these words had a 69.5% recognition rate, improving to about a 92% recognition rate after adaptation. A novel hybrid method is presented with a rate of about 77.2%.

  6. Digital filters

    CERN Document Server

    Hamming, Richard W

    1997-01-01

    Digital signals occur in an increasing number of applications: in telephone communications; in radio, television, and stereo sound systems; and in spacecraft transmissions, to name just a few. This introductory text examines digital filtering, the processes of smoothing, predicting, differentiating, integrating, and separating signals, as well as the removal of noise from a signal. The processes bear particular relevance to computer applications, one of the focuses of this book.Readers will find Hamming's analysis accessible and engaging, in recognition of the fact that many people with the s

  7. A Record Book of Open Heart Surgical Cases between 1959 and 1982, Hand-Written by a Cardiac Surgeon.

    Science.gov (United States)

    Kim, Won-Gon

    2016-08-01

    A book of brief records of open heart surgery underwent between 1959 and 1982 at Seoul National University Hospital was recently found. The book was hand-written by the late professor and cardiac surgeon Yung Kyoon Lee (1921-1994). This book contains valuable information about cardiac patients and surgery at the early stages of the establishment of open heart surgery in Korea, and at Seoul National University Hospital. This report is intended to analyze the content of the book.

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

    Science.gov (United States)

    Yoshikawa, Takatoshi; Okamoto, Masayosi; Horii, Hiroshi

    1993-04-01

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

  9. Word Spotting and Recognition with Embedded Attributes.

    Science.gov (United States)

    Almazán, Jon; Gordo, Albert; Fornés, Alicia; Valveny, Ernest

    2014-12-01

    This paper addresses the problems of word spotting and word recognition on images. In word spotting, the goal is to find all instances of a query word in a dataset of images. In recognition, the goal is to recognize the content of the word image, usually aided by a dictionary or lexicon. We describe an approach in which both word images and text strings are embedded in a common vectorial subspace. This is achieved by a combination of label embedding and attributes learning, and a common subspace regression. In this subspace, images and strings that represent the same word are close together, allowing one to cast recognition and retrieval tasks as a nearest neighbor problem. Contrary to most other existing methods, our representation has a fixed length, is low dimensional, and is very fast to compute and, especially, to compare. We test our approach on four public datasets of both handwritten documents and natural images showing results comparable or better than the state-of-the-art on spotting and recognition tasks.

  10. Speech Recognition on Mobile Devices

    DEFF Research Database (Denmark)

    Tan, Zheng-Hua; Lindberg, Børge

    2010-01-01

    The enthusiasm of deploying automatic speech recognition (ASR) on mobile devices is driven both by remarkable advances in ASR technology and by the demand for efficient user interfaces on such devices as mobile phones and personal digital assistants (PDAs). This chapter presents an overview of ASR...... in the mobile context covering motivations, challenges, fundamental techniques and applications. Three ASR architectures are introduced: embedded speech recognition, distributed speech recognition and network speech recognition. Their pros and cons and implementation issues are discussed. Applications within...... command and control, text entry and search are presented with an emphasis on mobile text entry....

  11. 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

  12. Digital speech processing using Matlab

    CERN Document Server

    Gopi, E S

    2014-01-01

    Digital Speech Processing Using Matlab deals with digital speech pattern recognition, speech production model, speech feature extraction, and speech compression. The book is written in a manner that is suitable for beginners pursuing basic research in digital speech processing. Matlab illustrations are provided for most topics to enable better understanding of concepts. This book also deals with the basic pattern recognition techniques (illustrated with speech signals using Matlab) such as PCA, LDA, ICA, SVM, HMM, GMM, BPN, and KSOM.

  13. Reducing weight precision of convolutional neural networks towards large-scale on-chip image recognition

    Science.gov (United States)

    Ji, Zhengping; Ovsiannikov, Ilia; Wang, Yibing; Shi, Lilong; Zhang, Qiang

    2015-05-01

    In this paper, we develop a server-client quantization scheme to reduce bit resolution of deep learning architecture, i.e., Convolutional Neural Networks, for image recognition tasks. Low bit resolution is an important factor in bringing the deep learning neural network into hardware implementation, which directly determines the cost and power consumption. We aim to reduce the bit resolution of the network without sacrificing its performance. To this end, we design a new quantization algorithm called supervised iterative quantization to reduce the bit resolution of learned network weights. In the training stage, the supervised iterative quantization is conducted via two steps on server - apply k-means based adaptive quantization on learned network weights and retrain the network based on quantized weights. These two steps are alternated until the convergence criterion is met. In this testing stage, the network configuration and low-bit weights are loaded to the client hardware device to recognize coming input in real time, where optimized but expensive quantization becomes infeasible. Considering this, we adopt a uniform quantization for the inputs and internal network responses (called feature maps) to maintain low on-chip expenses. The Convolutional Neural Network with reduced weight and input/response precision is demonstrated in recognizing two types of images: one is hand-written digit images and the other is real-life images in office scenarios. Both results show that the new network is able to achieve the performance of the neural network with full bit resolution, even though in the new network the bit resolution of both weight and input are significantly reduced, e.g., from 64 bits to 4-5 bits.

  14. Are Malaysian Students Ready to Be Authors of Digital Contents? A Case Study of Digital Library Stakeholders’ Readiness

    Directory of Open Access Journals (Sweden)

    Abrizah Abdullah

    2007-09-01

    Full Text Available The paper reports on a study that ascertains the factors facilitating students to utilize digital libraries for educational purposes. The study investigates students ICT readiness, usage of online resources and information seeking behaviour of secondary school students with the specific goal of applying the results to the design of a collaborative digital library for school projects. The digital library has been conceived to support resource needs of these students as well provide the space for them to publish their school projects, which are currently submitted handwritten. The study uses the case study approach and an urban secondary school in Malaysia is chosen as the case school. Findings from a survey and focus group interviews indicate that the students are ready to collaboratively build the digital library resources as evidenced by students digital library readiness score of 31.4/40.

  15. A Record Book of Open Heart Surgical Cases between 1959 and 1982, Hand-Written by a Cardiac Surgeon

    Directory of Open Access Journals (Sweden)

    Won-Gon Kim

    2016-08-01

    Full Text Available A book of brief records of open heart surgery underwent between 1959 and 1982 at Seoul National University Hospital was recently found. The book was hand-written by the late professor and cardiac surgeon Yung Kyoon Lee (1921–1994. This book contains valuable information about cardiac patients and surgery at the early stages of the establishment of open heart surgery in Korea, and at Seoul National University Hospital. This report is intended to analyze the content of the book.

  16. 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.

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

    Directory of Open Access Journals (Sweden)

    Laslo Dinges

    2016-03-01

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

  18. A word language model based contextual language processing on Chinese character recognition

    Science.gov (United States)

    Huang, Chen; Ding, Xiaoqing; Chen, Yan

    2010-01-01

    The language model design and implementation issue is researched in this paper. Different from previous research, we want to emphasize the importance of n-gram models based on words in the study of language model. We build up a word based language model using the toolkit of SRILM and implement it for contextual language processing on Chinese documents. A modified Absolute Discount smoothing algorithm is proposed to reduce the perplexity of the language model. The word based language model improves the performance of post-processing of online handwritten character recognition system compared with the character based language model, but it also increases computation and storage cost greatly. Besides quantizing the model data non-uniformly, we design a new tree storage structure to compress the model size, which leads to an increase in searching efficiency as well. We illustrate the set of approaches on a test corpus of recognition results of online handwritten Chinese characters, and propose a modified confidence measure for recognition candidate characters to get their accurate posterior probabilities while reducing the complexity. The weighted combination of linguistic knowledge and candidate confidence information proves successful in this paper and can be further developed to achieve improvements in recognition accuracy.

  19. An enhanced feature set for pattern recognition based contrast enhancement of contact-less captured latent fingerprints in digitized crime scene forensics

    Science.gov (United States)

    Hildebrandt, Mario; Kiltz, Stefan; Dittmann, Jana; Vielhauer, Claus

    2014-02-01

    In crime scene forensics latent fingerprints are found on various substrates. Nowadays primarily physical or chemical preprocessing techniques are applied for enhancing the visibility of the fingerprint trace. In order to avoid altering the trace it has been shown that contact-less sensors offer a non-destructive acquisition approach. Here, the exploitation of fingerprint or substrate properties and the utilization of signal processing techniques are an essential requirement to enhance the fingerprint visibility. However, especially the optimal sensory is often substrate-dependent. An enhanced generic pattern recognition based contrast enhancement approach for scans of a chromatic white light sensor is introduced in Hildebrandt et al.1 using statistical, structural and Benford's law2 features for blocks of 50 micron. This approach achieves very good results for latent fingerprints on cooperative, non-textured, smooth substrates. However, on textured and structured substrates the error rates are very high and the approach thus unsuitable for forensic use cases. We propose the extension of the feature set with semantic features derived from known Gabor filter based exemplar fingerprint enhancement techniques by suggesting an Epsilon-neighborhood of each block in order to achieve an improved accuracy (called fingerprint ridge orientation semantics). Furthermore, we use rotation invariant Hu moments as an extension of the structural features and two additional preprocessing methods (separate X- and Y Sobel operators). This results in a 408-dimensional feature space. In our experiments we investigate and report the recognition accuracy for eight substrates, each with ten latent fingerprints: white furniture surface, veneered plywood, brushed stainless steel, aluminum foil, "Golden-Oak" veneer, non-metallic matte car body finish, metallic car body finish and blued metal. In comparison to Hildebrandt et al.,1 our evaluation shows a significant reduction of the error rates

  20. Speech Recognition

    Directory of Open Access Journals (Sweden)

    Adrian Morariu

    2009-01-01

    Full Text Available This paper presents a method of speech recognition by pattern recognition techniques. Learning consists in determining the unique characteristics of a word (cepstral coefficients by eliminating those characteristics that are different from one word to another. For learning and recognition, the system will build a dictionary of words by determining the characteristics of each word to be used in the recognition. Determining the characteristics of an audio signal consists in the following steps: noise removal, sampling it, applying Hamming window, switching to frequency domain through Fourier transform, calculating the magnitude spectrum, filtering data, determining cepstral coefficients.

  1. Place Names of the Pelym River Area on Antal Reguly’s Handwritten Maps and the Etymologization of Mansi Toponyms

    Directory of Open Access Journals (Sweden)

    Tatiana N. Dmitrieva

    2017-03-01

    Full Text Available The article analyses toponymic data from the handwritten maps made in 1844–1845 by the outstanding Hungarian ethnographer and explorer Antal Reguly, that he later used as a basis for his famous Ethhnographic Map of the Northern Ural (1846. Reguly’s handwritten maps, still understudied, contain valuable toponymic information, considerably more detailed than in the final map, which makes them an important source of unique data on the toponymy of the region’s peoples in the 19th century. Based on previous research in the Pelym River toponymy (works by G. P. Vuono, G. V. Glinskikh, A. K. Matveyev, the materials of the explorations of G. F. Müller (1742, B. Munkácsi (1888–1889 and A. Kannisto (1901–1906, the fieldwork materials of the Ural University Toponymic Expedition, collected in 1960s–1970s, as well as on contemporary maps of the region, the author provides etymological interpretations of several toponyms of the Pelym River area whose Mansi population became completely Russified by the mid-20th century. The data retrieved from Antal Reguly’s maps serve to confirm the reliablity of previously suggested etymologies, to specify some of them, and to reconstruct the names that earlier failed to be etymologised.

  2. Fast Radioactive Nuclide Recognition Method Study Based on Pattern Recognition

    Directory of Open Access Journals (Sweden)

    Yonggang Huo

    2014-01-01

    Full Text Available Based on pattern recognition method, applied the nuclear radiation digital measurement and analysis system platform, through synthetically making use of the radioactive nuclide’s ray information, selected radiation characteristic information of the radioactive nuclide, established the characteristic arrays database of radioactive nuclides, the recognition method is designed and applied to the identification of radionuclide radiation while using middle or low-resolution detector in this paper. Verified by experiments, when the count value of the traditional low-resolution spectrometer system is not reach single full energy peak’s statistical lower limit value, the three kinds of mixed radioactive nuclides’ true discrimination rate reached more than 90 % in the digital measurement and analysis system using fast radionuclide recognition method. The results show that this method is obviously superior to the traditional methods, and effectively improve the rapid identification ability to radioactive nuclide.

  3. Reduction of the dimension of neural network models in problems of pattern recognition and forecasting

    Science.gov (United States)

    Nasertdinova, A. D.; Bochkarev, V. V.

    2017-11-01

    Deep neural networks with a large number of parameters are a powerful tool for solving problems of pattern recognition, prediction and classification. Nevertheless, overfitting remains a serious problem in the use of such networks. A method of solving the problem of overfitting is proposed in this article. This method is based on reducing the number of independent parameters of a neural network model using the principal component analysis, and can be implemented using existing libraries of neural computing. The algorithm was tested on the problem of recognition of handwritten symbols from the MNIST database, as well as on the task of predicting time series (rows of the average monthly number of sunspots and series of the Lorentz system were used). It is shown that the application of the principal component analysis enables reducing the number of parameters of the neural network model when the results are good. The average error rate for the recognition of handwritten figures from the MNIST database was 1.12% (which is comparable to the results obtained using the "Deep training" methods), while the number of parameters of the neural network can be reduced to 130 times.

  4. Facial Recognition

    National Research Council Canada - National Science Library

    Mihalache Sergiu; Stoica Mihaela-Zoica

    2014-01-01

    .... From birth, faces are important in the individual's social interaction. Face perceptions are very complex as the recognition of facial expressions involves extensive and diverse areas in the brain...

  5. Service evaluation of the implementation of a digitally-enabled care pathway for the recognition and management of acute kidney injury [version 2; referees: 2 approved

    Directory of Open Access Journals (Sweden)

    Alistair Connell

    2017-08-01

    Full Text Available Acute Kidney Injury (AKI, an abrupt deterioration in kidney function, is defined by changes in urine output or serum creatinine. AKI is common (affecting up to 20% of acute hospital admissions in the United Kingdom, associated with significant morbidity and mortality, and expensive (excess costs to the National Health Service in England alone may exceed £1 billion per year. NHS England has mandated the implementation of an automated algorithm to detect AKI based on changes in serum creatinine, and to alert clinicians. It is uncertain, however, whether ‘alerting’ alone improves care quality.   We have thus developed a digitally-enabled care pathway as a clinical service to inpatients in the Royal Free Hospital (RFH, a large London hospital. This pathway incorporates a mobile software application - the “Streams-AKI” app, developed by DeepMind Health - that applies the NHS AKI algorithm to routinely collected serum creatinine data in hospital inpatients. Streams-AKI alerts clinicians to potential AKI cases, furnishing them with a trend view of kidney function alongside other relevant data, in real-time, on a mobile device. A clinical response team comprising nephrologists and critical care nurses responds to these AKI alerts by reviewing individual patients and administering interventions according to existing clinical practice guidelines.   We propose a mixed methods service evaluation of the implementation of this care pathway. This evaluation will assess how the care pathway meets the health and care needs of service users (RFH inpatients, in terms of clinical outcome, processes of care, and NHS costs. It will also seek to assess acceptance of the pathway by members of the response team and wider hospital community. All analyses will be undertaken by the service evaluation team from UCL (Department of Applied Health Research and St George’s, University of London (Population Health Research Institute.

  6. Pattern recognition in the ALFALFA.70 and Sloan Digital Sky Surveys: a catalogue of ˜500 000 H I gas fraction estimates based on artificial neural networks

    Science.gov (United States)

    Teimoorinia, Hossen; Ellison, Sara L.; Patton, David R.

    2017-02-01

    The application of artificial neural networks (ANNs) for the estimation of H I gas mass fraction (M_{H I}/{{M}_{*}}) is investigated, based on a sample of 13 674 galaxies in the Sloan Digital Sky Survey (SDSS) with H I detections or upper limits from the Arecibo Legacy Fast Arecibo L-band Feed Array (ALFALFA). We show that, for an example set of fixed input parameters (g - r colour and I-band surface brightness), a multidimensional quadratic model yields M_{H I}/{{M}_{*}} scaling relations with a smaller scatter (0.22 dex) than traditional linear fits (0.32 dex), demonstrating that non-linear methods can lead to an improved performance over traditional approaches. A more extensive ANN analysis is performed using 15 galaxy parameters that capture variation in stellar mass, internal structure, environment and star formation. Of the 15 parameters investigated, we find that g - r colour, followed by stellar mass surface density, bulge fraction and specific star formation rate have the best connection with M_{H I}/{{M}_{*}}. By combining two control parameters, that indicate how well a given galaxy in SDSS is represented by the ALFALFA training set (PR) and the scatter in the training procedure (σfit), we develop a strategy for quantifying which SDSS galaxies our ANN can be adequately applied to, and the associated errors in the M_{H I}/{{M}_{*}} estimation. In contrast to previous works, our M_{H I}/{{M}_{*}} estimation has no systematic trend with galactic parameters such as M⋆, g - r and star formation rate. We present a catalogue of M_{H I}/{{M}_{*}} estimates for more than half a million galaxies in the SDSS, of which ˜150 000 galaxies have a secure selection parameter with average scatter in the M_{H I}/{{M}_{*}} estimation of 0.22 dex.

  7. Indoor navigation by image recognition

    Science.gov (United States)

    Choi, Io Teng; Leong, Chi Chong; Hong, Ka Wo; Pun, Chi-Man

    2017-07-01

    With the progress of smartphones hardware, it is simple on smartphone using image recognition technique such as face detection. In addition, indoor navigation system development is much slower than outdoor navigation system. Hence, this research proves a usage of image recognition technique for navigation in indoor environment. In this paper, we introduced an indoor navigation application that uses the indoor environment features to locate user's location and a route calculating algorithm to generate an appropriate path for user. The application is implemented on Android smartphone rather than iPhone. Yet, the application design can also be applied on iOS because the design is implemented without using special features only for Android. We found that digital navigation system provides better and clearer location information than paper map. Also, the indoor environment is ideal for Image recognition processing. Hence, the results motivate us to design an indoor navigation system using image recognition.

  8. Object Recognition with Stereo Vision and Geometric Hashing

    NARCIS (Netherlands)

    van Dijck, H.A.L.

    1999-01-01

    The subject of this thesis is the automatic recognition of objects from digital images. The discussion is restricted to recognition of man made objects that can be described by deterministic, structural models. Applications of this kind of recognition tasks can be found in industry. Object

  9. Usage of the back-propagation method for alphabet recognition

    Science.gov (United States)

    Shaila Sree, R. N.; Eswaran, Kumar; Sundararajan, N.

    1999-03-01

    Artificial Neural Networks play a pivotal role in the branch of Artificial Intelligence. They can be trained efficiently for a variety of tasks using different methods, of which the Back Propagation method is one among them. The paper studies the choosing of various design parameters of a neural network for the Back Propagation method. The study shows that when these parameters are properly assigned, the training task of the net is greatly simplified. The character recognition problem has been chosen as a test case for this study. A sample space of different handwritten characters of the English alphabet was gathered. A Neural net is finally designed taking many the design aspects into consideration and trained for different styles of writing. Experimental results are reported and discussed. It has been found that an appropriate choice of the design parameters of the neural net for the Back Propagation method reduces the training time and improves the performance of the net.

  10. Glyph Identification and Character Recognition for Sindhi OCR

    Directory of Open Access Journals (Sweden)

    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.

  11. The European Digital Kitchen Project

    OpenAIRE

    Seedhouse, Paul; Preston, Anne; Olivier, Patrick; Dan, Jackson; Philip, Heslop; Madeline, Balaam; Rafiev, Ashur; Kipling, Matthew

    2014-01-01

    This article reports on the European Digital Kitchen, an EU-funded language learning project which promotes learning of languages, cultures and cuisines in digital interactive kitchens. The project involves taking a normal kitchen and specifically adapting it for language learning using the next generation of digital technology, namely activity recognition and sensor technology. We intend that learners will be able to learn aspects of the language whilst performing a meaningful real-world tas...

  12. Whole-book recognition.

    Science.gov (United States)

    Xiu, Pingping; Baird, Henry S

    2012-12-01

    asymptotic accuracy is stable, even over long runs. If implemented naively, the algorithm runs in time quadratic in the length of the book, but random subsampling and caching techniques speed it up by two orders of magnitude with negligible loss of accuracy. Whole-book recognition has potential applications in digital libraries as a safe unsupervised anytime algorithm.

  13. Experiments on Urdu Text Recognition

    Science.gov (United States)

    Mukhtar, Omar; Setlur, Srirangaraj; Govindaraju, Venu

    Urdu is a language spoken in the Indian subcontinent by an estimated 130-270 million speakers. At the spoken level, Urdu and Hindi are considered dialects of a single language because of shared vocabulary and the similarity in grammar. At the written level, however, Urdu is much closer to Arabic because it is written in Nastaliq, the calligraphic style of the Persian-Arabic script. Therefore, a speaker of Hindi can understand spoken Urdu but may not be able to read written Urdu because Hindi is written in Devanagari script, whereas an Arabic writer can read the written words but may not understand the spoken Urdu. In this chapter we present an overview of written Urdu. Prior research in handwritten Urdu OCR is very limited. We present (perhaps) the first system for recognizing handwritten Urdu words. On a data set of about 1300 handwritten words, we achieved an accuracy of 70% for the top choice, and 82% for the top three choices.

  14. Ukrainian Cyrillic handwritten book of the XVII century from the fonds of theManuscript Institute of VNLU: codicological-paleographic study and description

    Directory of Open Access Journals (Sweden)

    Dobrianska T.

    2014-01-01

    Full Text Available The article provides the historiographical review of the main trends in contemporary codicological-paleographic study and description of the Ukrainian Cyrillic handwritten book of the XVII century, which is deposited in book gatherings and collections of the Manuscript Institute of V. Vernadsky National Library of Ukraine. The conducted historiographical analysis is a significant indicator of the given period manuscript heritage processing and description degree. The purpose of our work is to reveal the latest published descriptions of the Ukrainian codes of the ХVІІ century. In the publication we have determined the importance of the reviewed works in the modern scientific description of Ukrainian codes. We have noted that the Ukrainian Cyrillic handwritten book of the XVII century has not yet become a definite object of the historical codicologicaland source studies, has not been properly processed as a complex and has not been studied as a phenomenon of the general Ukrainian handwritten book culture so far. It is still necessary to study the latest published descriptions of Ukrainian codes for future researches.

  15. Facial Recognition

    Directory of Open Access Journals (Sweden)

    Mihalache Sergiu

    2014-05-01

    Full Text Available During their lifetime, people learn to recognize thousands of faces that they interact with. Face perception refers to an individual's understanding and interpretation of the face, particularly the human face, especially in relation to the associated information processing in the brain. The proportions and expressions of the human face are important to identify origin, emotional tendencies, health qualities, and some social information. From birth, faces are important in the individual's social interaction. Face perceptions are very complex as the recognition of facial expressions involves extensive and diverse areas in the brain. Our main goal is to put emphasis on presenting human faces specialized studies, and also to highlight the importance of attractiviness in their retention. We will see that there are many factors that influence face recognition.

  16. Massively parallel implementation of character recognition systems

    Science.gov (United States)

    Garris, Michael D.; Wilson, Charles L.; Blue, James L.; Candela, Gerald T.; Grother, Patrick J.; Janet, Stanley A.; Wilkinson, R. A.

    1992-08-01

    A massively parallel character recognition system has been implemented. The system is designed to study the feasibility of the recognition of handprinted text in a loosely constrained environment. The NIST handprint database, NIST Special Database 1, is used to provide test data for the recognition system. The system consists of eight functional components. The loading of the image into the system and storing the recognition results from the system are I/O components. In between are components responsible for image processing and recognition. The first image processing component is responsible for image correction for scale and rotation, data field isolation, and character data location within each field; the second performs character segmentation; and the third does character normalization. Three recognition components are responsible for feature extraction and character reconstruction, neural network-based character recognition, and low-confidence classification rejection. The image processing to load and isolate 34 fields on a scientific workstation takes 900 seconds. The same processing takes only 11 seconds using a massively parallel array processor. The image processing components, including the time to load the image data, use 94 of the system time. The segmentation time is 15 ms/character and segmentation accuracy is 89 for handprinted digits and alphas. Character recognition accuracy for medium quality machine print is 99.8. On handprinted digits, the recognition accuracy is 96 and recognition speeds of 10,100 characters/second can be realized. The limiting factor in the recognition portion of the system is feature extraction, which occurs at 806 characters/second. Through the use of a massively parallel machine and neural recognition algorithms, significant improvements in both accuracy and speed have been achieved, making this technology effective as a replacement for key data entry in existing data capture systems.

  17. The Interaction between Central and Peripheral Processing in Chinese Handwritten Production: Evidence from the Effect of Lexicality and Radical Complexity

    Science.gov (United States)

    Zhang, Qingfang; Feng, Chen

    2017-01-01

    The interaction between central and peripheral processing in written word production remains controversial. This study aims to investigate whether the effects of radical complexity and lexicality in central processing cascade into peripheral processing in Chinese written word production. The participants were asked to write characters and non-characters (lexicality) with different radical complexity (few- and many-strokes). The findings indicated that regardless of the lexicality, the writing latencies were longer for characters with higher complexity (the many-strokes condition) than for characters with lower complexity (the few-strokes condition). The participants slowed down their writing execution at the radicals' boundary strokes, which indicated a radical boundary effect in peripheral processing. Interestingly, the lexicality and the radical complexity affected the pattern of shift velocity and writing velocity during the execution of writing. Lexical processing cascades into peripheral processing but only at the beginning of Chinese characters. In contrast, the radical complexity influenced the execution of handwriting movement throughout the entire character, and the pattern of the effect interacted with the character frequency. These results suggest that the processes of the lexicality and the radical complexity function during the execution of handwritten word production, which suggests that central processing cascades over peripheral processing during Chinese characters handwriting. PMID:28348536

  18. Digital Note-Taking: Discussion of Evidence and Best Practices.

    Science.gov (United States)

    Grahame, Jason A

    2016-03-01

    Balancing active course engagement and comprehension with producing quality lecture notes is challenging. Although evidence suggests that handwritten note-taking may improve comprehension and learning outcomes, many students still self-report a preference for digital note-taking and a belief that it is beneficial. Future research is warranted to determine the effects on performance of digitally writing notes. Independent of the methods or software chosen, best practices should be provided to students with information to help them consciously make an educated decision based on the evidence and their personal preference. Optimal note-taking requires self-discipline, focused attention, sufficient working memory, thoughtful rewording, and decreased distractions. Familiarity with the tools and mediums they choose will help students maximize working memory, produce better notes, and aid in their retention of material presented.

  19. Speaker Recognition

    DEFF Research Database (Denmark)

    Mølgaard, Lasse Lohilahti; Jørgensen, Kasper Winther

    2005-01-01

    Speaker recognition is basically divided into speaker identification and speaker verification. Verification is the task of automatically determining if a person really is the person he or she claims to be. This technology can be used as a biometric feature for verifying the identity of a person...... in applications like banking by telephone and voice mail. The focus of this project is speaker identification, which consists of mapping a speech signal from an unknown speaker to a database of known speakers, i.e. the system has been trained with a number of speakers which the system can recognize....

  20. On Recognition

    DEFF Research Database (Denmark)

    Gjødsbøl, Iben Mundbjerg; Svendsen, Mette Nordahl

    2017-01-01

    to misrecognize and humiliate the person under examination. The article ends by proposing that dementia be the condition that forces us to rethink our ways of recognizing persons more generally. Thus, dementia diagnostics provide insights into different enactments of the person that invite us to explore practices......This article investigates how a person with dementia is made up through intersubjective acts of recognition. Based on ethnographic fieldwork in a Danish memory clinic, we show that identification of disease requires patients to be substituted by their relatives in constructing believable medical...

  1. SAR: Stroke Authorship Recognition

    KAUST Repository

    Shaheen, Sara

    2015-10-15

    Are simple strokes unique to the artist or designer who renders them? If so, can this idea be used to identify authorship or to classify artistic drawings? Also, could training methods be devised to develop particular styles? To answer these questions, we propose the Stroke Authorship Recognition (SAR) approach, a novel method that distinguishes the authorship of 2D digitized drawings. SAR converts a drawing into a histogram of stroke attributes that is discriminative of authorship. We provide extensive classification experiments on a large variety of data sets, which validate SAR\\'s ability to distinguish unique authorship of artists and designers. We also demonstrate the usefulness of SAR in several applications including the detection of fraudulent sketches, the training and monitoring of artists in learning a particular new style and the first quantitative way to measure the quality of automatic sketch synthesis tools. © 2015 The Eurographics Association and John Wiley & Sons Ltd.

  2. Digital image analysis

    DEFF Research Database (Denmark)

    Riber-Hansen, Rikke; Vainer, Ben; Steiniche, Torben

    2012-01-01

    Digital image analysis (DIA) is increasingly implemented in histopathological research to facilitate truly quantitative measurements, decrease inter-observer variation and reduce hands-on time. Originally, efforts were made to enable DIA to reproduce manually obtained results on histological slides...... optimized for light microscopy and the human eye. With improved technical methods and the acknowledgement that computerized readings are different from analysis by human eye, recognition has been achieved that to really empower DIA, histological slides must be optimized for the digital 'eye...... reproducibility, application of stereology-based quantitative measurements, time consumption, optimization of histological slides, regions of interest selection and recent developments in staining and imaging techniques....

  3. Digital imaging in anatomic pathology.

    Science.gov (United States)

    O'Brien, M J; Sotnikov, A V

    1996-10-01

    Advances in computer technology continue to bring new innovations to departments of anatomic pathology. This article briefly reviews the present status of digital optical imaging, and explores the directions that this technology may lead over the next several years. Technical requirements for digital microscopic and gross imaging, and the available options for image archival and retrieval are summarized. The advantages of digital images over conventional photography in the conference room, and the usefulness of digital imaging in the frozen section suite and gross room, as an adjunct to surgical signout and as a resource for training and education, are discussed. An approach to the future construction of digital histologic sections and the computer as microscope is described. The digital technologic applications that are now available as components of the surgical pathologist's workstation are enumerated. These include laboratory information systems, computerized voice recognition, and on-line or CD-based literature searching, texts and atlases and, in some departments, on-line image databases. The authors suggest that, in addition to these resources that are already available, tomorrow's surgical pathology workstation will include network-linked digital histologic databases, on-line software for image analysis and 3-D image enhancement, expert systems, and ultimately, advanced pattern recognition capabilities. In conclusion, the authors submit that digital optical imaging is likely to have a significant and positive impact on the future development of anatomic pathology.

  4. Eye movement analysis for activity recognition using electrooculography.

    Science.gov (United States)

    Bulling, Andreas; Ward, Jamie A; Gellersen, Hans; Tröster, Gerhard

    2011-04-01

    In this work, we investigate eye movement analysis as a new sensing modality for activity recognition. Eye movement data were recorded using an electrooculography (EOG) system. We first describe and evaluate algorithms for detecting three eye movement characteristics from EOG signals-saccades, fixations, and blinks-and propose a method for assessing repetitive patterns of eye movements. We then devise 90 different features based on these characteristics and select a subset of them using minimum redundancy maximum relevance (mRMR) feature selection. We validate the method using an eight participant study in an office environment using an example set of five activity classes: copying a text, reading a printed paper, taking handwritten notes, watching a video, and browsing the Web. We also include periods with no specific activity (the NULL class). Using a support vector machine (SVM) classifier and person-independent (leave-one-person-out) training, we obtain an average precision of 76.1 percent and recall of 70.5 percent over all classes and participants. The work demonstrates the promise of eye-based activity recognition (EAR) and opens up discussion on the wider applicability of EAR to other activities that are difficult, or even impossible, to detect using common sensing modalities.

  5. Automatic TLI recognition system beta prototype testing

    Energy Technology Data Exchange (ETDEWEB)

    Lassahn, G.D.

    1996-06-01

    This report describes the beta prototype automatic target recognition system ATR3, and some performance tests done with this system. This is a fully operational system, with a high computational speed. It is useful for findings any kind of target in digitized image data, and as a general purpose image analysis tool.

  6. Military applications of automatic speech recognition and future requirements

    Science.gov (United States)

    Beek, Bruno; Cupples, Edward J.

    1977-01-01

    An updated summary of the state-of-the-art of automatic speech recognition and its relevance to military applications is provided. A number of potential systems for military applications are under development. These include: (1) digital narrowband communication systems; (2) automatic speech verification; (3) on-line cartographic processing unit; (4) word recognition for militarized tactical data system; and (5) voice recognition and synthesis for aircraft cockpit.

  7. Digital food photography

    National Research Council Canada - National Science Library

    Manna, Lou; Moss, Bill

    2005-01-01

    ... . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 The Digital Age . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 The Digital Process...

  8. Digital squares

    DEFF Research Database (Denmark)

    Forchhammer, Søren; Kim, Chul E

    1988-01-01

    Digital squares are defined and their geometric properties characterized. A linear time algorithm is presented that considers a convex digital region and determines whether or not it is a digital square. The algorithm also determines the range of the values of the parameter set of its preimages. ....... The analysis involves transforming the boundary of a digital region into parameter space of slope and y-intercept......Digital squares are defined and their geometric properties characterized. A linear time algorithm is presented that considers a convex digital region and determines whether or not it is a digital square. The algorithm also determines the range of the values of the parameter set of its preimages...

  9. Facial Recognition in a Group-Living Cichlid Fish.

    Directory of Open Access Journals (Sweden)

    Masanori Kohda

    Full Text Available The theoretical underpinnings of the mechanisms of sociality, e.g. territoriality, hierarchy, and reciprocity, are based on assumptions of individual recognition. While behavioural evidence suggests individual recognition is widespread, the cues that animals use to recognise individuals are established in only a handful of systems. Here, we use digital models to demonstrate that facial features are the visual cue used for individual recognition in the social fish Neolamprologus pulcher. Focal fish were exposed to digital images showing four different combinations of familiar and unfamiliar face and body colorations. Focal fish attended to digital models with unfamiliar faces longer and from a further distance to the model than to models with familiar faces. These results strongly suggest that fish can distinguish individuals accurately using facial colour patterns. Our observations also suggest that fish are able to rapidly (≤ 0.5 sec discriminate between familiar and unfamiliar individuals, a speed of recognition comparable to primates including humans.

  10. Introduction of statistical information in a syntactic analyzer for document image recognition

    Science.gov (United States)

    Maroneze, André O.; Coüasnon, Bertrand; Lemaitre, Aurélie

    2011-01-01

    This paper presents an improvement to document layout analysis systems, offering a possible solution to Sayre's paradox (which states that an element "must be recognized before it can be segmented; and it must be segmented before it can be recognized"). This improvement, based on stochastic parsing, allows integration of statistical information, obtained from recognizers, during syntactic layout analysis. We present how this fusion of numeric and symbolic information in a feedback loop can be applied to syntactic methods to improve document description expressiveness. To limit combinatorial explosion during exploration of solutions, we devised an operator that allows optional activation of the stochastic parsing mechanism. Our evaluation on 1250 handwritten business letters shows this method allows the improvement of global recognition scores.

  11. Using features of local densities, statistics and HMM toolkit (HTK for offline Arabic handwriting text recognition

    Directory of Open Access Journals (Sweden)

    El Moubtahij Hicham

    2017-12-01

    Full Text Available This paper presents an analytical approach of an offline handwritten Arabic text recognition system. It is based on the Hidden Markov Models (HMM Toolkit (HTK without explicit segmentation. The first phase is preprocessing, where the data is introduced in the system after quality enhancements. Then, a set of characteristics (features of local densities and features statistics are extracted by using the technique of sliding windows. Subsequently, the resulting feature vectors are injected to the Hidden Markov Model Toolkit (HTK. The simple database “Arabic-Numbers” and IFN/ENIT are used to evaluate the performance of this system. Keywords: Hidden Markov Models (HMM Toolkit (HTK, Sliding windows

  12. Digital Culture and Digital Library

    Directory of Open Access Journals (Sweden)

    Yalçın Yalçınkaya

    2016-12-01

    Full Text Available In this study; digital culture and digital library which have a vital connection with each other are examined together. The content of the research consists of the interaction of culture, information, digital culture, intellectual technologies, and digital library concepts. The study is an entry work to integrity of digital culture and digital library theories and aims to expand the symmetry. The purpose of the study is to emphasize the relation between the digital culture and digital library theories acting intersection of the subjects that are examined. Also the perspective of the study is based on examining the literature and analytical evaluation in both studies (digital culture and digital library. Within this context, the methodology of the study is essentially descriptive and has an attribute for the transmission and synthesis of distributed findings produced in the field of the research. According to the findings of the study results, digital culture is an inclusive term that describes the effects of intellectual technologies in the field of information and communication. Information becomes energy and the spectrum of the information is expanding in the vertical rise through the digital culture. In this context, the digital library appears as a new living space of a new environment. In essence, the digital library is information-oriented; has intellectual technology support and digital platform; is in a digital format; combines information resources and tools in relationship/communication/cooperation by connectedness, and also it is the dynamic face of the digital culture in time and space independence. Resolved with the study is that the digital libraries are active and effective in the formation of global knowing and/or mass wisdom in the process of digital culture.

  13. Digital Insights

    DEFF Research Database (Denmark)

    Knudsen, Gry Høngsmark

    This dissertation forwards the theory of digital consumer-response as a perspective to examine how digital media practices influence consumers’ response to advertising. Digital consumer-response is a development of advertising theory that encompasses how consumers employ their knowledge...... and practices with digital media, when they meet and interpret advertising. Through studies of advertising response on YouTube and experiments with consumers’ response to digitally manipulated images, the dissertation shows how digital media practices facilitate polysemic and socially embedded advertising...... response. The dissertation argues that digital consumer-response changes our understanding of texts, contexts, consumers, and agency, because digital consumer-response operates with a discursive analytical perspective, as opposed to the micro-textual analyses of much advertising research. Further...

  14. Quantum Digital Signatures for Unconditional Safe Authenticity Protection of Medical Documentation

    Directory of Open Access Journals (Sweden)

    Arkadiusz Liber

    2015-12-01

    Full Text Available Modern medical documentation appears most often in an online form which requires some digital methods to ensure its confidentiality, integrity and authenticity. The document authenticity may be secured with the use of a signature. A classical handwritten signature is directly related to its owner by his/her psychomotor character traits. Such a signature is also connected with the material it is written on, and a writing tool. Because of these properties, a handwritten signature reflects certain close material bonds between the owner and the document. In case of modern digital signatures, the document authentication has a mathematical nature. The verification of the authenticity becomes the verification of a key instead of a human. Since 1994 it has been known that classical digital signature algorithms may not be safe because of the Shor’s factorization algorithm. To implement the modern authenticity protection of medical data, some new types of algorithms should be used. One of the groups of such algorithms is based on the quantum computations. In this paper, the analysis of the current knowledge status of Quantum Digital Signature protocols, with its basic principles, phases and common elements such as transmission, comparison and encryption, was outlined. Some of the most promising protocols for signing digital medical documentation, that fulfill the requirements for QDS, were also briefly described. We showed that, a QDS protocol with QKD components requires the equipment similar to the equipment used for a QKD, for its implementation, which is already commercially available. If it is properly implemented, it provides the shortest lifetime of qubits in comparison to other protocols. It can be used not only to sign classical messages but probably it could be well adopted to implement unconditionally safe protection of medical documentation in the nearest future, as well.

  15. Digital Tectonics

    DEFF Research Database (Denmark)

    Christiansen, Karl; Borup, Ruben; Søndergaard, Asbjørn

    2014-01-01

    Digital Tectonics treats the architectonical possibilities in digital generation of form and production. The publication is the first volume of a series, in which aspects of the strategic focus areas of the Aarhus School of Architecture will be disseminated.......Digital Tectonics treats the architectonical possibilities in digital generation of form and production. The publication is the first volume of a series, in which aspects of the strategic focus areas of the Aarhus School of Architecture will be disseminated....

  16. Digital Citizenship

    Science.gov (United States)

    Isman, Aytekin; Canan Gungoren, Ozlem

    2014-01-01

    Era in which we live is known and referred as digital age.In this age technology is rapidly changed and developed. In light of these technological advances in 21st century, schools have the responsibility of training "digital citizen" as well as a good citizen. Digital citizens must have extensive skills, knowledge, Internet and …

  17. DIGITAL FORGERY

    OpenAIRE

    Sarhan M. Musa1

    2017-01-01

    Forgery is the criminal act that provides misleading information about a product or service. It is the process of making, adapting, or imitating documents or objects with the intent to deceive. Digital forgery (or digital tampering) is the process of manipulating documents or images for the intent of financial, social or political gain. This paper provides a brief introduction to the digital forgery.

  18. Digital preservation

    CERN Document Server

    Deegan, Marilyn

    2013-01-01

    Digital preservation is an issue of huge importance to the library and information profession right now. With the widescale adoption of the internet and the rise of the world wide web, the world has been overwhelmed by digital information. Digital data is being produced on a massive scale by individuals and institutions: some of it is born, lives and dies only in digital form, and it is the potential death of this data, with its impact on the preservation of culture, that is the concern of this book. So how can information professionals try to remedy this? Digital preservation is a complex iss

  19. Image Recognition Using Modified Zernike Moments

    Directory of Open Access Journals (Sweden)

    Min HUANG

    2014-03-01

    Full Text Available Zernike moments are complex moments with the orthogonal Zernike polynomials as kernel function, compared with other moments; Zernike moments have greater advantages in image rotation and low noise sensitivity. Because of the Zernike moments have image rotation invariance, and can construct arbitrary high order moments, it can be used for target recognition. In this paper, the Zernike moment algorithm is improved, which makes it having scale invariance in the processing of digital image. At last, an application of the improved Zernike moments in image recognition is given.

  20. Object reading: text recognition for object recognition

    NARCIS (Netherlands)

    Karaoglu, S.; van Gemert, J.C.; Gevers, T.

    2012-01-01

    We propose to use text recognition to aid in visual object class recognition. To this end we first propose a new algorithm for text detection in natural images. The proposed text detection is based on saliency cues and a context fusion step. The algorithm does not need any parameter tuning and can

  1. Digital Natives or Digital Tribes?

    Science.gov (United States)

    Watson, Ian Robert

    2013-01-01

    This research builds upon the discourse surrounding digital natives. A literature review into the digital native phenomena was undertaken and found that researchers are beginning to identify the digital native as not one cohesive group but of individuals influenced by other factors. Primary research by means of questionnaire survey of technologies…

  2. Digital color imaging

    CERN Document Server

    Fernandez-Maloigne, Christine; Macaire, Ludovic

    2013-01-01

    This collective work identifies the latest developments in the field of the automatic processing and analysis of digital color images.For researchers and students, it represents a critical state of the art on the scientific issues raised by the various steps constituting the chain of color image processing.It covers a wide range of topics related to computational color imaging, including color filtering and segmentation, color texture characterization, color invariant for object recognition, color and motion analysis, as well as color image and video indexing and retrieval. <

  3. Face Detection and Recognition

    National Research Council Canada - National Science Library

    Jain, Anil K

    2004-01-01

    This report describes research efforts towards developing algorithms for a robust face recognition system to overcome many of the limitations found in existing two-dimensional facial recognition systems...

  4. Multi-stream HMM for EMG-based speech recognition.

    Science.gov (United States)

    Manabe, H; Zhang, Z

    2004-01-01

    A technique for improving the recognition accuracy of EMG-based speech recognition by applying existing speech recognition technologies is proposed. The authors have proposed an EMG-based speech recognition system that requires only mouth movements, voice need not be generated. A multi-stream HMM (hidden Markov model) and feature extraction technique are applied to EMG-based speech recognition. 3 channel facial EMG signals are collected from ten subjects when uttering 10 Japanese isolated digits. One channel corresponds to one stream. By examining various features, we found that the delta component of the static parameter leads to higher accuracy. Compared to equal stream weighting, the individual optimization of stream weights increased recognition accuracy by 4.0% which corresponds to a 12.8% reduction in error rate. This result shows that multistream HMM is effective for the classification of EMG.

  5. Embedded Face Detection and Recognition

    Directory of Open Access Journals (Sweden)

    Göksel Günlü

    2012-10-01

    Full Text Available The need to increase security in open or public spaces has in turn given rise to the requirement to monitor these spaces and analyse those images on-site and on-time. At this point, the use of smart cameras – of which the popularity has been increasing – is one step ahead. With sensors and Digital Signal Processors (DSPs, smart cameras generate ad hoc results by analysing the numeric images transmitted from the sensor by means of a variety of image-processing algorithms. Since the images are not transmitted to a distance processing unit but rather are processed inside the camera, it does not necessitate high-bandwidth networks or high processor powered systems; it can instantaneously decide on the required access. Nonetheless, on account of restricted memory, processing power and overall power, image processing algorithms need to be developed and optimized for embedded processors. Among these algorithms, one of the most important is for face detection and recognition. A number of face detection and recognition methods have been proposed recently and many of these methods have been tested on general-purpose processors. In smart cameras – which are real-life applications of such methods – the widest use is on DSPs. In the present study, the Viola-Jones face detection method – which was reported to run faster on PCs – was optimized for DSPs; the face recognition method was combined with the developed sub-region and mask-based DCT (Discrete Cosine Transform. As the employed DSP is a fixed-point processor, the processes were performed with integers insofar as it was possible. To enable face recognition, the image was divided into sub-regions and from each sub-region the robust coefficients against disruptive elements – like face expression, illumination, etc. – were selected as the features. The discrimination of the selected features was enhanced via LDA (Linear Discriminant Analysis and then employed for recognition. Thanks to its

  6. Digital Forensics

    OpenAIRE

    Garfinkel, Simson L.

    2013-01-01

    A reprint from American Scientist the magazine of Sigma Xi, The Scientific Research Society Since the 1980s, computers have had increasing roles in all aspects of human life—including an involvement in criminal acts. This development has led to the rise of digital forensics, the uncovering and examination of evidence located on all things electronic with digital storage, including computers, cell phones, and networks. Digital forensics researchers and practitione...

  7. Signatura digital

    OpenAIRE

    Vila Mateos, Carlos

    2011-01-01

    Aquest projecte tracta la Signatura Digital des del punt de vista d'un Enginyer de Software que ha d'iniciar un projecte que doni serveis de Signatura Digital a un projecte més ampli d'Administració Electrònica. El projecte contempla: els conceptes bàsics de la Signatura Digital, les particularitats de la Signatura Digital, les funcionalitats i serveis que pot proporcionar a una plataforma de tramitació electrònica, els requeriments de Signatura Electrònica per l'AE, la selecció d'un prov...

  8. Digital Literacy to parents in the use of social networks

    National Research Council Canada - National Science Library

    Nidia Milena Moreno López; Angie Carolina González Robles; Ana Carolina Torres Gómez; Julissa Araya Hernández

    2017-01-01

    The present article has as objective to describe the process of digital literacy directed at the parents of family in the recognition and use of social networks, in the educational institution Coopteboy...

  9. Digital Audiobooks

    DEFF Research Database (Denmark)

    Have, Iben; Pedersen, Birgitte Stougaard

    Audiobooks are rapidly gaining popularity with widely accessible digital downloading and streaming services. The paper is framing how the digital audiobook expands and changes the target groups for book publications and how it as an everyday activity is creating new reading experiences, places...

  10. Digital bioanalysis.

    Science.gov (United States)

    Miller, Elizabeth M; Wheeler, Aaron R

    2009-01-01

    Digital microfluidics has recently emerged as a new paradigm in the world of lab-on-a-chip technology. A wide variety of bioanalyses have been successfully implemented in this format. This paper reviews the various techniques that have been adapted to digital microfluidic systems, and the current state of the field.

  11. Digital TMI

    Science.gov (United States)

    Rios, Joseph

    2012-01-01

    Presenting the current status of the Digital TMI project to visiting members of the FAA Command Center. Digital TMI is an effort to store national-level traffic management initiatives in a standards-compliant manner. Work is funded by the FAA.

  12. Digital Images and Human Vision

    Science.gov (United States)

    Watson, Andrew B.; Null, Cynthia H. (Technical Monitor)

    1997-01-01

    Processing of digital images destined for visual consumption raises many interesting questions regarding human visual sensitivity. This talk will survey some of these questions, including some that have been answered and some that have not. There will be an emphasis upon visual masking, and a distinction will be drawn between masking due to contrast gain control processes, and due to processes such as hypothesis testing, pattern recognition, and visual search.

  13. Sports Digitalization

    DEFF Research Database (Denmark)

    Xiao, Xiao; Hedman, Jonas; Tan, Felix Ter Chian

    2017-01-01

    Ever since its first manifesto in Greece around 3000 years ago, sports as a field has accumulated a long history with strong traditions while at the same time, gone through tremendous changes toward professionalization and commercialization. The current waves of digitalization have intensified its...... evolution, as digital technologies are increasingly entrenched in a wide range of sporting activities and for applications beyond mere performance enhancement. Despite such trends, research on sports digitalization in the IS discipline is surprisingly still nascent. This paper aims at establishing...... a discourse on sports digitalization within the discipline. Toward this, we first provide an understanding of the institutional Sports Digitalization Thirty Eighth International Conference on Information Systems, Seoul 2017 2 characteristics of the sports industry, establishing its theoretical importance...

  14. Digital displacements

    DEFF Research Database (Denmark)

    Pors, Anja Svejgaard

    2014-01-01

    digital interface. However, the transformation of citizen services from traditional face-to-face interaction to digital self-service gives rise to new practices; some citizens need support to be able to manage self-service through digital tools. A mixture of support and teaching, named co...... digital reforms in Denmark and shows how citizen service is transformed from service to support. The frontline employee’s classical tasks such as casework are being displaced into educational and support-oriented tasks with less professional content. Thus an unintended effect of digitisation is blurred......In recent years digital reforms are being introduced in the municipal landscape of Denmark. The reforms address the interaction between citizen and local authority. The aim is, that by 2015 at least 80 per cent of all correspondence between citizens and public authority will be transmitted through...

  15. Standard digital reference images for titanium castings

    CERN Document Server

    American Society for Testing and Materials. Philadelphia

    2010-01-01

    1.1 The digital reference images provided in the adjunct to this standard illustrate various types and degrees of discontinuities occurring in titanium castings. Use of this standard for the specification or grading of castings requires procurement of the adjunct digital reference images, which illustrate the discontinuity types and severity levels. They are intended to provide the following: 1.1.1 A guide enabling recognition of titanium casting discontinuities and their differentiation both as to type and degree through digital radiographic examination. 1.1.2 Example digital radiographic illustrations of discontinuities and a nomenclature for reference in acceptance standards, specifications and drawings. 1.2 The digital reference images consist of seventeen digital files each illustrating eight grades of increasing severity. The files illustrate seven common discontinuity types representing casting sections up to 1-in. (25.4-mm). 1.3 The reference radiographs were developed for casting sections up to 1...

  16. Multimodal eye recognition

    Science.gov (United States)

    Zhou, Zhi; Du, Yingzi; Thomas, N. L.; Delp, Edward J., III

    2010-04-01

    Multimodal biometrics use more than one means of biometric identification to achieve higher recognition accuracy, since sometimes a unimodal biometric is not good enough used to do identification and classification. In this paper, we proposed a multimodal eye recognition system, which can obtain both iris and sclera patterns from one color eye image. Gabor filter and 1-D Log-Gabor filter algorithms have been applied as the iris recognition algorithms. In sclera recognition, we introduced automatic sclera segmentation, sclera pattern enhancement, sclera pattern template generation, and sclera pattern matching. We applied kernelbased matching score fusion to improve the performance of the eye recognition system. The experimental results show that the proposed eye recognition method can achieve better performance compared to unimodal biometric identification, and the accuracy of our proposed kernel-based matching score fusion method is higher than two classic linear matching score fusion methods: Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA).

  17. Pattern recognition & machine learning

    CERN Document Server

    Anzai, Y

    1992-01-01

    This is the first text to provide a unified and self-contained introduction to visual pattern recognition and machine learning. It is useful as a general introduction to artifical intelligence and knowledge engineering, and no previous knowledge of pattern recognition or machine learning is necessary. Basic for various pattern recognition and machine learning methods. Translated from Japanese, the book also features chapter exercises, keywords, and summaries.

  18. Recognition and Toleration

    DEFF Research Database (Denmark)

    Lægaard, Sune

    2010-01-01

    Recognition and toleration are ways of relating to the diversity characteristic of multicultural societies. The article concerns the possible meanings of toleration and recognition, and the conflict that is often claimed to exist between these two approaches to diversity. Different forms or inter......Recognition and toleration are ways of relating to the diversity characteristic of multicultural societies. The article concerns the possible meanings of toleration and recognition, and the conflict that is often claimed to exist between these two approaches to diversity. Different forms...

  19. Statistical Pattern Recognition

    CERN Document Server

    Webb, Andrew R

    2011-01-01

    Statistical pattern recognition relates to the use of statistical techniques for analysing data measurements in order to extract information and make justified decisions.  It is a very active area of study and research, which has seen many advances in recent years. Applications such as data mining, web searching, multimedia data retrieval, face recognition, and cursive handwriting recognition, all require robust and efficient pattern recognition techniques. This third edition provides an introduction to statistical pattern theory and techniques, with material drawn from a wide range of fields,

  20. Digital electronics

    CERN Document Server

    Morris, John

    2013-01-01

    An essential companion to John C Morris's 'Analogue Electronics', this clear and accessible text is designed for electronics students, teachers and enthusiasts who already have a basic understanding of electronics, and who wish to develop their knowledge of digital techniques and applications. Employing a discovery-based approach, the author covers fundamental theory before going on to develop an appreciation of logic networks, integrated circuit applications and analogue-digital conversion. A section on digital fault finding and useful ic data sheets completes th

  1. Digital holography

    CERN Document Server

    Picart, Pascal

    2013-01-01

    This book presents a substantial description of the principles and applications of digital holography.The first part of the book deals with mathematical basics and the linear filtering theory necessary to approach the topic. The next part describes the fundamentals of diffraction theory and exhaustively details the numerical computation of diffracted fields using FFT algorithms. A thorough presentation of the principles of holography and digital holography, including digital color holography, is proposed in the third part.A special section is devoted to the algorithms and method

  2. Digital Leadership

    DEFF Research Database (Denmark)

    Zupancic, Tadeja; Verbeke, Johan; Achten, Henri

    2016-01-01

    . With this paper we intend to initiate a discussion in the eCAADe community to reflect and develop ideas in order to develop digital leadership skills amongst the membership. This paper introduces some important aspects, which may be valuable to look into when developing digital leadership skills.......Leadership is an important quality in organisations. Leadership is needed to introduce change and innovation. In our opinion, in architectural and design practices, the role of leadership has not yet been sufficiently studied, especially when it comes to the role of digital tools and media...

  3. Dynamic Features for Iris Recognition.

    Science.gov (United States)

    da Costa, R M; Gonzaga, A

    2012-08-01

    The human eye is sensitive to visible light. Increasing illumination on the eye causes the pupil of the eye to contract, while decreasing illumination causes the pupil to dilate. Visible light causes specular reflections inside the iris ring. On the other hand, the human retina is less sensitive to near infra-red (NIR) radiation in the wavelength range from 800 nm to 1400 nm, but iris detail can still be imaged with NIR illumination. In order to measure the dynamic movement of the human pupil and iris while keeping the light-induced reflexes from affecting the quality of the digitalized image, this paper describes a device based on the consensual reflex. This biological phenomenon contracts and dilates the two pupils synchronously when illuminating one of the eyes by visible light. In this paper, we propose to capture images of the pupil of one eye using NIR illumination while illuminating the other eye using a visible-light pulse. This new approach extracts iris features called "dynamic features (DFs)." This innovative methodology proposes the extraction of information about the way the human eye reacts to light, and to use such information for biometric recognition purposes. The results demonstrate that these features are discriminating features, and, even using the Euclidean distance measure, an average accuracy of recognition of 99.1% was obtained. The proposed methodology has the potential to be "fraud-proof," because these DFs can only be extracted from living irises.

  4. Digitizing Villanova University's Eclipsing Binary Card Catalogue

    Science.gov (United States)

    Guzman, Giannina; Dalton, Briana; Conroy, Kyle; Prsa, Andrej

    2018-01-01

    Villanova University’s Department of Astrophysics and Planetary Science has years of hand-written archival data on Eclipsing Binaries at its disposal. This card catalog began at Princeton in the 1930’s with notable contributions from scientists such as Henry Norris Russel. During World War II, the archive was moved to the University of Pennsylvania, which was one of the world centers for Eclipsing Binary research, consequently, the contributions to the catalog during this time were immense. It was then moved to University of Florida at Gainesville before being accepted by Villanova in the 1990’s. The catalog has been kept in storage since then. The objective of this project is to digitize this archive and create a fully functional online catalog that contains the information available on the cards, along with the scan of the actual cards. Our group has built a database using a python-powered infrastructure to contain the collected data. The team also built a prototype web-based searchable interface as a front-end to the catalog. Following the data-entry process, information like the Right Ascension and Declination will be run against SIMBAD and any differences between values will be noted as part of the catalog. Information published online from the card catalog and even discrepancies in information for a star, could be a catalyst for new studies on these Eclipsing Binaries. Once completed, the database-driven interface will be made available to astronomers worldwide. The group will also acquire, from the database, a list of referenced articles that have yet to be found online in order to further pursue their digitization. This list will be comprised of references in the cards that were neither found on ADS nor online during the data-entry process. Pursuing the integration of these references to online queries such as ADS will be an ongoing process that will contribute and further facilitate studies on Eclipsing Binaries.

  5. Digital food photography

    National Research Council Canada - National Science Library

    Manna, Lou; Moss, Bill

    2005-01-01

    ... . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 2 Digital Photography: The Necessities 21 Selecting a Digital Camera and Accessories...

  6. Digital Discretion

    DEFF Research Database (Denmark)

    Busch, Peter Andre; Zinner Henriksen, Helle

    2018-01-01

    discretion is suggested to reduce this footprint by influencing or replacing their discretionary practices using ICT. What is less researched is whether digital discretion can cause changes in public policy outcomes, and under what conditions such changes can occur. Using the concept of public service values......This study reviews 44 peer-reviewed articles on digital discretion published in the period from 1998 to January 2017. Street-level bureaucrats have traditionally had a wide ability to exercise discretion stirring debate since they can add their personal footprint on public policies. Digital......, we suggest that digital discretion can strengthen ethical and democratic values but weaken professional and relational values. Furthermore, we conclude that contextual factors such as considerations made by policy makers on the macro-level and the degree of professionalization of street...

  7. Becoming digital

    DEFF Research Database (Denmark)

    Pors, Anja Svejgaard

    2015-01-01

    . Originality/value: The study contributes to ethnographic research in public administration by combining two separate subfields, e-government and street-level bureaucracy, to discern recent transformations in public service delivery. In the digital era, tasks, control and equality are distributed in ways......The purpose of this paper is to examine the impact of e-government reforms on street-level bureaucrats’ professionalism and relation to citizens, thus demonstrating how the bureaucratic encounter unfolds in the digital era. Design/methodology/approach: The paper is based on an ethnographic study....... An ethnographic account of how digital reforms are implemented in practice shows how street-level bureaucrat’s classic tasks such as specialized casework are being reconfigured into educational tasks that promote the idea of “becoming digital”. In the paper, the author argues that the work of “becoming digital...

  8. Digital Humanities

    DEFF Research Database (Denmark)

    Brügger, Niels

    2016-01-01

    Digital humanities is an umbrella term for theories, methodologies, and practices related to humanities scholarship that use the digital computer as an integrated and essential part of its research and teaching activities. The computer can be used for establishing, finding, collecting......, and preserving material to study, as an object of study in its own right, as an analytical tool, or for collaborating, and for disseminating results. The term "digital humanities" was coined around 2001, and gained currency within academia in the following years. However, computers had been used within...... the humanities for decades, starting with research fields such as humanities computing or computational linguistics in the 1950s, and later new media studies and internet studies. The historical development of digital humanities has been characterized by a focus on three successive, but co-existing types...

  9. Digital Snaps

    DEFF Research Database (Denmark)

    Sandbye, Mette; Larsen, Jonas

    The New Face of Snapshot Photography / Jonas Larsen and Mette Sandbye -- pt. I. IMAGES ON WEB 2.0 AND THE CAMERA PHONE -- ch. 1. Overlooking, Rarely Looking and Not Looking / Martin Lister -- ch. 2. The (Im)mobile Life of Digital Photographs: The Case of Tourist Photography / Jonas Larsen -- ch. 3....... Distance as the New Punctum / Mikko Villi -- pt. II. FAMILY ALBUMS IN TRANSITION -- ch. 4. How Digital Technologies Do Family Snaps, Only Better / Gillian Rose -- ch. 5. Friendship Photography: Memory, Mobility and Social Networking / Joanne Garde-Hansen -- ch. 6. Play, Process and Materiality in Japanese...... Purikura Photography / Mette Sandbye -- ch. 7. 'Buying an Instrument Does Not Necessarily Make You a Musician': Studio Photography and the Digital Revolution / Sigrid Lien -- pt. III. NEW PUBLIC FORMS -- ch. 8 Paparazzi Photography, Seriality and the Digital Photo Archive / Anne Jerslev and Mette Mortensen...

  10. Digital fabrication

    CERN Document Server

    2012-01-01

    The Winter 2012 (vol. 14 no. 3) issue of the Nexus Network Journal features seven original papers dedicated to the theme “Digital Fabrication”. Digital fabrication is changing architecture in fundamental ways in every phase, from concept to artifact. Projects growing out of research in digital fabrication are dependent on software that is entirely surface-oriented in its underlying mathematics. Decisions made during design, prototyping, fabrication and assembly rely on codes, scripts, parameters, operating systems and software, creating the need for teams with multidisciplinary expertise and different skills, from IT to architecture, design, material engineering, and mathematics, among others The papers grew out of a Lisbon symposium hosted by the ISCTE-Instituto Universitario de Lisboa entitled “Digital Fabrication – A State of the Art”. The issue is completed with four other research papers which address different mathematical instruments applied to architecture, including geometric tracing system...

  11. Digital Steganography

    OpenAIRE

    KOCIÁNOVÁ, Helena

    2009-01-01

    Digital steganography is a technique for hiding data mostly into multimedia files (images, audio, video). With the development of information technology this technique has found its use in the field of copyright protection and secret data transfer, could be even applied in places where is limited possibility of using cryptography (e. g. by law). This thesis gives insight into digital steganography and contains an application using this technique.

  12. Digital video.

    Science.gov (United States)

    Johnson, Don; Johnson, Mike

    2004-04-01

    The process of digital capture, editing, and archiving video has become an important aspect of documenting arthroscopic surgery. Recording the arthroscopic findings before and after surgery is an essential part of the patient's medical record. The hardware and software has become more reasonable to purchase, but the learning curve to master the software is steep. Digital video is captured at the time of arthroscopy to a hard disk, and written to a CD at the end of the operative procedure. The process of obtaining video of open procedures is more complex. Outside video of the procedure is recorded on digital tape with a digital video camera. The camera must be plugged into a computer to capture the video on the hard disk. Adobe Premiere software is used to edit the video and render the finished video to the hard drive. This finished video is burned onto a CD. We outline the choice of computer hardware and software for the manipulation of digital video. The techniques of backup and archiving the completed projects and files also are outlined. The uses of digital video for education and the formats that can be used in PowerPoint presentations are discussed.

  13. Determination of Digital Straight Segments Using the Slope

    OpenAIRE

    Cartas, Alejandro; Algorri, María Elena

    2018-01-01

    We present a new method for the recognition of digital straight lines based on the slope. This method combines the Freeman's chain coding scheme and new discovered properties of the digital slope introduced in this paper. We also present the efficiency of our method from a testbed.

  14. Recognition and Toleration

    DEFF Research Database (Denmark)

    Lægaard, Sune

    2010-01-01

    Recognition and toleration are ways of relating to the diversity characteristic of multicultural societies. The article concerns the possible meanings of toleration and recognition, and the conflict that is often claimed to exist between these two approaches to diversity. Different forms or inter...

  15. Recognition as care

    DEFF Research Database (Denmark)

    Ahlmark, Nanna; Whyte, Susan Reynolds; Harting, Janneke

    2014-01-01

    -based and solidarity-based recognition to analyse what was at stake in these experiences, and we engage Annemarie Mol’s concept of a logic of care to show how recognition unfolded practically during the training. We propose that participants’ wider social context and experiences of misrecognition situated the training...

  16. Challenging ocular image recognition

    Science.gov (United States)

    Pauca, V. Paúl; Forkin, Michael; Xu, Xiao; Plemmons, Robert; Ross, Arun A.

    2011-06-01

    Ocular recognition is a new area of biometric investigation targeted at overcoming the limitations of iris recognition performance in the presence of non-ideal data. There are several advantages for increasing the area beyond the iris, yet there are also key issues that must be addressed such as size of the ocular region, factors affecting performance, and appropriate corpora to study these factors in isolation. In this paper, we explore and identify some of these issues with the goal of better defining parameters for ocular recognition. An empirical study is performed where iris recognition methods are contrasted with texture and point operators on existing iris and face datasets. The experimental results show a dramatic recognition performance gain when additional features are considered in the presence of poor quality iris data, offering strong evidence for extending interest beyond the iris. The experiments also highlight the need for the direct collection of additional ocular imagery.

  17. Análise discriminante paramétrica para reconhecimento de defeitos em tábuas de eucalipto utilizando imagens digitais Parametric discriminant analysis for recognition of defects in eucalyptus lumber using digital images

    Directory of Open Access Journals (Sweden)

    Joseph Kalil Khoury Junior

    2005-04-01

    work was to evaluate, using multivariate analysis, the discriminating power of color images percents. In this work, linear and quadratic discriminant analysis were accomplished for classification of defects and clear wood in digital images of eucalyptus lumber. The percent features of the histogram for the red, green and blue bands, from two sizes of image blocks were used for developing and testing the discriminant functions. 492 blocks were used, containing the 12 studied defects and clear wood, derived from images of 40 lumbers randomly sampled. The features were analyzed with their original values, scores of the principal components and scores of the canonical variables. The smallest global misclassification errors were 19% and 24% for linear discriminant function with the canonical variable scores using block sizes of 64x64 and 32x32 pixels, respectively. The percent features were considered appropriate to discriminate defects and clear wood in digital images.

  18. Speculative Method in Digital Education Research

    Science.gov (United States)

    Ross, Jen

    2017-01-01

    The question of "what works" is currently dominating educational research, often to the exclusion of other kinds of inquiries and without enough recognition of its limitations. At the same time, digital education practice, policy and research over-emphasises control, efficiency and enhancement, neglecting the "not-yetness" of…

  19. Ekstraksi Ciri Batang untuk Pengenalan Nomer Rekening Tulisan Tangan dengan Jaringan Syaraf Tiruan Perambatan Balik

    Directory of Open Access Journals (Sweden)

    Farida Asriani

    2012-02-01

    Full Text Available Handwriting number recognition was being challenge problem to do in the recent years. The main objective for our research waso recognized handwritten account number. The original data was bank deposit slip that acquired by scanner. Before do the recognition of account number handwritten, first step that must be done was located account number on the bank deposit slip. After the location was found then the account number was segmented to cut up each numbern. After cutting the stem then performed feature extraction to obtain a vector which was fed to the neural network system for recognition rate. System back propagation neural network for handwritten digit pattern recognition was designed by 168neuron consists of input layer, 70 neurons in the hidden layer and 10 neurons in the output layer. The results obtained in this study were 83.78% of the data slip can be recognized correctly.

  20. Digital evidence

    Directory of Open Access Journals (Sweden)

    Lukić Tatjana

    2012-01-01

    Full Text Available Although computer makes human activities faster and easier, innovating and creating new forms of work and other kinds of activities, it also influenced the criminal activity. The development of information technology directly affects the development of computer forensics without which, it can not even imagine the discovering and proving the computer offences and apprehending the perpetrator. Information technology and computer forensic allows us to detect and prove the crimes committed by computer and capture the perpetrators. Computer forensics is a type of forensics which can be defined as a process of collecting, preserving, analyzing and presenting digital evidence in court proceedings. Bearing in mind, that combat against crime, in which computers appear as an asset or object of the offense, requires knowledge of digital evidence as well as specific rules and procedures, the author in this article specifically addresses the issues of digital evidence, forensic (computer investigation, specific rules and procedures for detecting, fixing and collecting digital evidence and use of this type of evidence in criminal proceedings. The author also delas with international standards regarding digital evidence and cyber-space investigation.

  1. Digital watermark

    Directory of Open Access Journals (Sweden)

    Jasna Maver

    2000-01-01

    Full Text Available The huge amount of multimedia contents available on the World-Wide-Web is beginning to raise the question of their protection. Digital watermarking is a technique which can serve various purposes, including intellectual property protection, authentication and integrity verification, as well as visible or invisible content labelling of multimedia content. Due to the diversity of digital watermarking applicability, there are many different techniques, which can be categorised according to different criteria. A digital watermark can be categorised as visible or invisible and as robust or fragile. In contrast to the visible watermark where a visible pattern or image is embedded into the original image, the invisible watermark does not change the visual appearance of the image. The existence of such a watermark can be determined only through a watermark ex¬traction or detection algorithm. The robust watermark is used for copyright protection, while the fragile watermark is designed for authentication and integrity verification of multimedia content. A watermark must be detectable or extractable to be useful. In some watermarking schemes, a watermark can be extracted in its exact form, in other cases, we can detect only whether a specific given watermarking signal is present in an image. Digital libraries, through which cultural institutions will make multimedia contents available, should support a wide range of service models for intellectual property protection, where digital watermarking may play an important role.

  2. [Does the digital signature of the DICOM standard meet the requirements of German law?].

    Science.gov (United States)

    Schütze, B; Kroll, M; Geisbe, T; Braun, M; Filler, T J

    2003-08-01

    The DICOM standard offers the possibilities to generate electronic signatures, valid according to German laws. This enhances the reliability of the correlation between image and patient data. However, only so called qualified electronic signatures--conveniently issued by an accredited supplier--are permissible and not rejectable as evidence in German jurisdiction and are completely equivalent to the handwritten signatures. These qualified electronic signatures can be executed only by individuals, whereas the former are not applicable to technical apparatus like image generating modalities. In consequence, a modality is able to provide its pictures with a "common or advanced signature" solely. This limits the use of the digital signature of the DICOM standard for further applications, e.g. the verifiability within the teleradiology.

  3. Recognition: Conceptualization and Context

    DEFF Research Database (Denmark)

    Gimmler, Antje

    2017-01-01

    be evaluated. In the first section, I will introduce the concept of recognition as a travelling concept playing a role both on the intellectual stage and in real life. In the second section, I will concentrate on the presentation of Honneth’s theory of recognition, emphasizing the construction of the concept......In this article, I shall examine the cognitive, heuristic and theoretical functions of the concept of recognition. To evaluate both the explanatory power and the limitations of a sociological concept, the theory construction must be analysed and its actual productivity for sociological theory must...

  4. Digital Creativity

    DEFF Research Database (Denmark)

    Petersson Brooks, Eva; Brooks, Anthony Lewis

    2014-01-01

    This paper reports on a study exploring the outcomes from children’s play with technology in early childhood learning practices. The paper addresses questions related to how digital technology can foster creativity in early childhood learning environments. It consists of an analysis of children......’s interaction with the KidSmart furniture focusing on digital creativity potentials and play values suggested by the technology. The study applied a qualitative approach and included125 children (aged three to five), 10 pedagogues, and two librarians. The results suggests that educators should sensitively...... consider intervening when children are interacting with technology, and rather put emphasize into the integration of the technology into the environment and to the curriculum in order to shape playful structures for children’s digital creativity....

  5. Digital "X"

    DEFF Research Database (Denmark)

    Baiyere, Abayomi; Grover, Varun; Gupta, Alok

    2017-01-01

    Interest in using digital before existing research concepts seem to be on the rise in the IS field. This panel is positioned to explore what value lies in labelling our research as digital “x” as opposed to the well established IT “x” (where “x” can be strategy, infrastructure, innovation, artifact......, capability e.t.c). The question this raises is that of how much this contributes novel insight to IS scholarship versus how much this is merely a relabeling of old wines in new wine bottles. The panel is expected to provide conceptual clarity on the use of the digital “x” concept and provide a delineation...

  6. Digital Relationships

    DEFF Research Database (Denmark)

    Ledborg Hansen, Richard

    -­‐Jones, 2011) for increases in effectiveness and efficiency we indiscriminately embrace digital communication and digitized information dissemination with enthusiasm – at the risk of ignoring the potentially dark side of technology. However, technology also holds a promise for better understanding precisely...... of residual deposits from technology in organizations and its effect on individuals ability to connect to one another. Based on the case study the paper describes indications and suggests potential implication hereof. Given the inherent enhancement possibilities of technology our expectation for entertainment......-­rich information and highly interesting communication are sky-­high and rising. With a continuous increase in digitized communication follows a decrease in face-­to-­face encounters and our ability to engage in inter-­personal relationships are suffering for it (Davis, 2013). The behavior described in this paper...

  7. Digital Radiography

    Science.gov (United States)

    1986-01-01

    System One, a digital radiography system, incorporates a reusable image medium (RIM) which retains an image. No film is needed; the RIM is read with a laser scanner, and the information is used to produce a digital image on an image processor. The image is stored on an optical disc. System allows the radiologist to "dial away" unwanted images to compare views on three screens. It is compatible with existing equipment and cost efficient. It was commercialized by a Stanford researcher from energy selective technology developed under a NASA grant.

  8. Digital communication

    CERN Document Server

    Das, Apurba

    2010-01-01

    ""Digital Communications"" presents the theory and application of the philosophy of Digital Communication systems in a unique but lucid form. This book inserts equal importance to the theory and application aspect of the subject whereby the authors selected a wide class of problems. The Salient features of the book are: the foundation of Fourier series, Transform and wavelets are introduces in a unique way but in lucid language; the application area is rich and resemblance to the present trend of research, as we are attached with those areas professionally; a CD is included which contains code

  9. Digital literacies

    CERN Document Server

    Hockly, Nicky; Pegrum, Mark

    2014-01-01

    Dramatic shifts in our communication landscape have made it crucial for language teaching to go beyond print literacy and encompass the digital literacies which are increasingly central to learners' personal, social, educational and professional lives. By situating these digital literacies within a clear theoretical framework, this book provides educators and students alike with not just the background for a deeper understanding of these key 21st-century skills, but also the rationale for integrating these skills into classroom practice. This is the first methodology book to address not jus

  10. Digital photogrammetry

    CERN Document Server

    Egels, Yves

    2003-01-01

    Photogrammetry is the use of photography for surveying primarily and is used for the production of maps from aerial photographs. Along with remote sensing, it represents the primary means of generating data for Geographic Information Systems (GIS). As technology develops, it is becoming easier to gain access to it. The cost of digital photogrammetric workstations are falling quickly and these new tools are therefore becoming accessible to more and more users. Digital Photogrammetry is particularly useful as a text for graduate students in geomantic and is also suitable for people with a good basic scientific knowledge who need to understand photogrammetry, and who wish to use the book as a reference.

  11. Machine Recognition vs Human Recognition of Voices

    Science.gov (United States)

    2012-05-01

    been studied for a while. For example, an early reference [1] is from 1966. 10 male speakers were recorded and their voices were presented to 16... recognized . The accuracy of speaker recognition for disyllables was 87%. For monosyllables, it was 81%, consonant-vowel excerpts were 63%, and...vowel excerpts were 56%. Thus, they demonstrated that the identification performance decreased as the number of phonemes decreased. In [2], the

  12. Compact Acoustic Models for Embedded Speech Recognition

    Directory of Open Access Journals (Sweden)

    Lévy Christophe

    2009-01-01

    Full Text Available Speech recognition applications are known to require a significant amount of resources. However, embedded speech recognition only authorizes few KB of memory, few MIPS, and small amount of training data. In order to fit the resource constraints of embedded applications, an approach based on a semicontinuous HMM system using state-independent acoustic modelling is proposed. A transformation is computed and applied to the global model in order to obtain each HMM state-dependent probability density functions, authorizing to store only the transformation parameters. This approach is evaluated on two tasks: digit and voice-command recognition. A fast adaptation technique of acoustic models is also proposed. In order to significantly reduce computational costs, the adaptation is performed only on the global model (using related speaker recognition adaptation techniques with no need for state-dependent data. The whole approach results in a relative gain of more than 20% compared to a basic HMM-based system fitting the constraints.

  13. Face photo-sketch synthesis and recognition.

    Science.gov (United States)

    Wang, Xiaogang; Tang, Xiaoou

    2009-11-01

    In this paper, we propose a novel face photo-sketch synthesis and recognition method using a multiscale Markov Random Fields (MRF) model. Our system has three components: 1) given a face photo, synthesizing a sketch drawing; 2) given a face sketch drawing, synthesizing a photo; and 3) searching for face photos in the database based on a query sketch drawn by an artist. It has useful applications for both digital entertainment and law enforcement. We assume that faces to be studied are in a frontal pose, with normal lighting and neutral expression, and have no occlusions. To synthesize sketch/photo images, the face region is divided into overlapping patches for learning. The size of the patches decides the scale of local face structures to be learned. From a training set which contains photo-sketch pairs, the joint photo-sketch model is learned at multiple scales using a multiscale MRF model. By transforming a face photo to a sketch (or transforming a sketch to a photo), the difference between photos and sketches is significantly reduced, thus allowing effective matching between the two in face sketch recognition. After the photo-sketch transformation, in principle, most of the proposed face photo recognition approaches can be applied to face sketch recognition in a straightforward way. Extensive experiments are conducted on a face sketch database including 606 faces, which can be downloaded from our Web site (http://mmlab.ie.cuhk.edu.hk/facesketch.html).

  14. Algebraic pattern recognition

    Science.gov (United States)

    Przybyłek, Michał R.

    2014-01-01

    This paper offers an algebraic explanation for the phenomenon of a new and prosperous branch of evolutionary metaheuristics - "skeletal algorithms". We show how this explanation gives rise to algorithms for recognition of algebraic theories and present sample applications.

  15. Forensic speaker recognition

    NARCIS (Netherlands)

    Meuwly, Didier

    2013-01-01

    The aim of forensic speaker recognition is to establish links between individuals and criminal activities, through audio speech recordings. This field is multidisciplinary, combining predominantly phonetics, linguistics, speech signal processing, and forensic statistics. On these bases, expert-based

  16. Automatic speech recognition systems

    Science.gov (United States)

    Catariov, Alexandru

    2005-02-01

    In this paper is presented analyses in automatic speech recognition (ASR) to find out what is the state of the arts in this direction and, eventually, it can be a starting point for the implementation of a real ASR system. In the second chapter of this work, it is revealed the structure of a typical speech recognition system and the used methods for each step of the recognition process, and in special, there are described two kinds of speech recognition algorithms, namely, Dynamic Time Warping (DTW) and Hidden Markov Model (HMM). The work continues with some results of ASR, in order to make conclusions about what is needed to be improved and what is more eligible to implement an ASR system.

  17. Work and Recognition

    DEFF Research Database (Denmark)

    Willig, Rasmus

    2004-01-01

    individual and collective identity formation and has led to an increase in social pathological illnesses such as stress and depression. By juxtaposing these analyses with Honneth’s theory on recognition, we conclude that the contemporary logic of work is unable to provide adequate forms of recognition......The article deals with the relationship between work and recognition, taking Axel Honneth’s social-philosophical theory of the struggle for recognition as its point of departure. In order to give sociological substance to Honneth’s theory, we turn to three contemporary social theorists - Jean......-Pierre Le Goff, Christophe Dejours and Emmanuel Renault. In spite of many differences, their work is united by a critical description of the logic of work and its consequences for individual individuation. These theorists agree that the growth of autonomy, flexibility and mobility has destabilised...

  18. Evaluating music emotion recognition

    DEFF Research Database (Denmark)

    Sturm, Bob L.

    2013-01-01

    A fundamental problem with nearly all work in music genre recognition (MGR)is that evaluation lacks validity with respect to the principal goals of MGR. This problem also occurs in the evaluation of music emotion recognition (MER). Standard approaches to evaluation, though easy to implement, do...... not reliably differentiate between recognizing genre or emotion from music, or by virtue of confounding factors in signals (e.g., equalization). We demonstrate such problems for evaluating an MER system, and conclude with recommendations....

  19. The Recognition Of Fatigue

    DEFF Research Database (Denmark)

    Elsass, Peter; Jensen, Bodil; Mørup, Rikke

    2007-01-01

    Elsass P., Jensen B., Morup R., Thogersen M.H. (2007). The Recognition Of Fatigue: A qualitative study of life-stories from rehabilitation clients. International Journal of Psychosocial Rehabilitation. 11 (2), 75-87......Elsass P., Jensen B., Morup R., Thogersen M.H. (2007). The Recognition Of Fatigue: A qualitative study of life-stories from rehabilitation clients. International Journal of Psychosocial Rehabilitation. 11 (2), 75-87...

  20. Character Recognition (Devanagari Script)

    OpenAIRE

    Ankita Karia; Sonali Sharma

    2015-01-01

    Character Recognition is has found major interest in field of research and practical application to analyze and study characters in different languages using image as their input. In this paper the user writes the Devanagari character using mouse as a plotter and then the corresponding character is saved in the form of image. This image is processed using Optical Character Recognition in which location, segmentation, pre-processing of image is done. Later Neural Networks is used t...

  1. Why recognition is rational

    Directory of Open Access Journals (Sweden)

    Clintin P. Davis-Stober

    2010-07-01

    Full Text Available The Recognition Heuristic (Gigerenzer and Goldstein, 1996; Goldstein and Gigerenzer, 2002 makes the counter-intuitive prediction that a decision maker utilizing less information may do as well as, or outperform, an idealized decision maker utilizing more information. We lay a theoretical foundation for the use of single-variable heuristics such as the Recognition Heuristic as an optimal decision strategy within a linear modeling framework. We identify conditions under which over-weighting a single predictor is a mini-max strategy among a class of a priori chosen weights based on decision heuristics with respect to a measure of statistical lack of fit we call ``risk''. These strategies, in turn, outperform standard multiple regression as long as the amount of data available is limited. We also show that, under related conditions, weighting only one variable and ignoring all others produces the same risk as ignoring the single variable and weighting all others. This approach has the advantage of generalizing beyond the original environment of the Recognition Heuristic to situations with more than two choice options, binary or continuous representations of recognition, and to other single variable heuristics. We analyze the structure of data used in some prior recognition tasks and find that it matches the sufficient conditions for optimality in our results. Rather than being a poor or adequate substitute for a compensatory model, the Recognition Heuristic closely approximates an optimal strategy when a decision maker has finite data about the world.

  2. Digital books.

    Science.gov (United States)

    Wink, Diane M

    2011-01-01

    In this bimonthly series, the author examines how nurse educators can use the Internet and Web-based computer technologies such as search, communication, and collaborative writing tools; social networking and social bookmarking sites; virtual worlds; and Web-based teaching and learning programs. This article describes digital books.

  3. Digital Methods

    NARCIS (Netherlands)

    Rogers, R.

    2013-01-01

    In Digital Methods, Richard Rogers proposes a methodological outlook for social and cultural scholarly research on the Web that seeks to move Internet research beyond the study of online culture. It is not a toolkit for Internet research, or operating instructions for a software package; it deals

  4. Digital Forensics

    Science.gov (United States)

    Harron, Jason; Langdon, John; Gonzalez, Jennifer; Cater, Scott

    2017-01-01

    The term forensic science may evoke thoughts of blood-spatter analysis, DNA testing, and identifying molds, spores, and larvae. A growing part of this field, however, is that of digital forensics, involving techniques with clear connections to math and physics. This article describes a five-part project involving smartphones and the investigation…

  5. Digital Badges

    Science.gov (United States)

    Frederiksen, Linda

    2013-01-01

    Unlike so much of the current vocabulary in education and technology that seems to stir more confusion than clarity, most public service librarians may already have a general idea about digital badges. As visual representations of individual accomplishments, competencies or skills that are awarded by groups, institutions, or organizations, they…

  6. Sports Digitalization

    DEFF Research Database (Denmark)

    Xiao, Xiao; Hedman, Jonas; Tan, Felix Ter Chian

    2017-01-01

    Ever since its first manifesto in Greece around 3000 years ago, sports as a field has accumulated a long history with strong traditions while at the same time, gone through tremendous changes toward professionalization and commercialization. The current waves of digitalization have intensified it...

  7. Digital forvaltning

    DEFF Research Database (Denmark)

    Remmen, Arne; Larsen, Torben; Mosgaard, Mette

    2004-01-01

    Større effektivitet, bedre service og mere demokrai er blot nogle af forventningerne til indførelse af digital forveltning i kommunerne. Kapitlet giver bland andet svar på spørgsmålene : Hvordan lever kommunerne op hertil i dagligdagen? hvilke virkemidler anvender de? Hvilke barrierer har der været...

  8. Digital Disruption

    DEFF Research Database (Denmark)

    Rosenstand, Claus Andreas Foss

    det digitale domæne ud over det niveau, der kendetegner den nuværende debat, så præsenteres der ny viden om digital disruption. Som noget nyt udlægges Clayton Christens teori om disruptiv innovation med et særligt fokus på små organisationers mulighed for eksponentiel vækst. Specielt udfoldes...... forholdet mellem disruption og den stadig accelererende digitale udvikling i konturerne til ny teoridannelse om digital disruption. Bogens undertitel ”faretruende og fascinerende forandringer” peger på, at der er behov for en nuanceret debat om digital disruption i modsætning til den tone, der er slået an i...... videre kalder et ”disruption-råd”. Faktisk er rådet skrevet ind i 2016 regeringsgrundlaget for VLK-regeringen. Disruption af organisationer er ikke et nyt fænomen; men hastigheden, hvormed det sker, er stadig accelererende. Årsagen er den globale mega-trend: Digitalisering. Og derfor er specielt digital...

  9. Mexican sign language recognition using normalized moments and artificial neural networks

    Science.gov (United States)

    Solís-V., J.-Francisco; Toxqui-Quitl, Carina; Martínez-Martínez, David; H.-G., Margarita

    2014-09-01

    This work presents a framework designed for the Mexican Sign Language (MSL) recognition. A data set was recorded with 24 static signs from the MSL using 5 different versions, this MSL dataset was captured using a digital camera in incoherent light conditions. Digital Image Processing was used to segment hand gestures, a uniform background was selected to avoid using gloved hands or some special markers. Feature extraction was performed by calculating normalized geometric moments of gray scaled signs, then an Artificial Neural Network performs the recognition using a 10-fold cross validation tested in weka, the best result achieved 95.83% of recognition rate.

  10. Digital Humanities and networked digital media

    Directory of Open Access Journals (Sweden)

    Niels Ole Finnemann

    2014-10-01

    Full Text Available This article discusses digital humanities and the growing diversity of digital media, digital materials and digital methods. The first section describes the humanities computing tradition formed around the interpretation of computation as a rule-based process connected to a concept of digital materials centred on the digitisation of non-digital, finite works, corpora and oeuvres. The second section discusses “the big tent” of contemporary digital humanities. It is argued that there can be no unifying interpretation of digital humanities above the level of studying digital materials with the help of software-supported methods. This is so, in part, because of the complexity of the world and, in part, because digital media remain open to the projection of new epistemologies onto the functional architecture of these media. The third section discusses the heterogeneous character of digital materials and proposes that the study of digital materials should be established as a field in its own right.

  11. Digital Humanities and networked digital media

    Directory of Open Access Journals (Sweden)

    Niels Ole Finnemann

    2014-12-01

    Full Text Available This article discusses digital humanities and the growing diversity of digital media, digital materials and digital methods. The first section describes the humanities computing tradition formed around the interpretation of computation as a rule-based process connected to a concept of digital materials centred on the digitisation of non-digital, finite works, corpora and oeuvres. The second section discusses “the big tent” of contemporary digital humanities. It is argued that there can be no unifying interpretation of digital humanities above the level of studying digital materials with the help of software-supported methods. This is so, in part, because of the complexity of the world and, in part, because digital media remain open to the projection of new epistemologies onto the functional architecture of these media. The third section discusses the heterogeneous character of digital materials and proposes that the study of digital materials should be established as a field in its own right.

  12. A Massively Parallel Face Recognition System

    Directory of Open Access Journals (Sweden)

    Ari Paasio

    2006-12-01

    Full Text Available We present methods for processing the LBPs (local binary patterns with a massively parallel hardware, especially with CNN-UM (cellular nonlinear network-universal machine. In particular, we present a framework for implementing a massively parallel face recognition system, including a dedicated highly accurate algorithm suitable for various types of platforms (e.g., CNN-UM and digital FPGA. We study in detail a dedicated mixed-mode implementation of the algorithm and estimate its implementation cost in the view of its performance and accuracy restrictions.

  13. A Massively Parallel Face Recognition System

    Directory of Open Access Journals (Sweden)

    Lahdenoja Olli

    2007-01-01

    Full Text Available We present methods for processing the LBPs (local binary patterns with a massively parallel hardware, especially with CNN-UM (cellular nonlinear network-universal machine. In particular, we present a framework for implementing a massively parallel face recognition system, including a dedicated highly accurate algorithm suitable for various types of platforms (e.g., CNN-UM and digital FPGA. We study in detail a dedicated mixed-mode implementation of the algorithm and estimate its implementation cost in the view of its performance and accuracy restrictions.

  14. Convolutional Neural Network for Image Recognition

    CERN Document Server

    Seifnashri, Sahand

    2015-01-01

    The aim of this project is to use machine learning techniques especially Convolutional Neural Networks for image processing. These techniques can be used for Quark-Gluon discrimination using calorimeters data, but unfortunately I didn’t manage to get the calorimeters data and I just used the Jet data fromminiaodsim(ak4 chs). The Jet data was not good enough for Convolutional Neural Network which is designed for ’image’ recognition. This report is made of twomain part, part one is mainly about implementing Convolutional Neural Network on unphysical data such as MNIST digits and CIFAR-10 dataset and part 2 is about the Jet data.

  15. Digital imaging technology assessment: Digital document storage project

    Science.gov (United States)

    1989-01-01

    An ongoing technical assessment and requirements definition project is examining the potential role of digital imaging technology at NASA's STI facility. The focus is on the basic components of imaging technology in today's marketplace as well as the components anticipated in the near future. Presented is a requirement specification for a prototype project, an initial examination of current image processing at the STI facility, and an initial summary of image processing projects at other sites. Operational imaging systems incorporate scanners, optical storage, high resolution monitors, processing nodes, magnetic storage, jukeboxes, specialized boards, optical character recognition gear, pixel addressable printers, communications, and complex software processes.

  16. 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

  17. 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%.

  18. Becoming digital

    DEFF Research Database (Denmark)

    Pors, Anja Svejgaard

    2015-01-01

    government, and draws on empirical material generated through observations, field notes, interviews and policy documents. The material is documenting how service is performed by frontline agents in the ‘bureaucratic encounter’ with citizens, who needs assistance to use digital self-service in order to apply...... online for a public benefit. Findings: The paper shows that e-government technology changes the mode of professionalism in citizen service from service to support. The paper gives an empirical account of recent Danish digital reforms and shows how the reforms both enable and constrain the work...... of ‘becoming digital’ by frontline agents. Overall the street-level bureaucrat’s classical tasks such as specialized casework are being displaced into promoting and educational tasks. An implication of this is blurred distinctions between professional skills and personal competences of the frontline agent...

  19. [Digital radiography].

    Science.gov (United States)

    Haendle, J

    1983-03-01

    Digital radiography is a generally accepted term comprising all x-ray image systems producing a projected image which resembles the conventional x-ray film image, and which are linked to any type of digital image processing. Fundamental criteria of differentiation are based on the production and detection method of the x-ray image. Various systems are employed, viz. the single-detector, line-detector or fanbeam detector and the area-beam or area-detector image converters, which differ from one another mainly in the manner of conversion of the radiation produced by the x-ray tube. The article also deals with the pros and cons of the various principles, the multitude of systems employed, and the varying frequency of their use in x-ray diagnosis work.

  20. Digital resources

    Directory of Open Access Journals (Sweden)

    Redazione Reti Medievali (a cura di

    2005-12-01

    Full Text Available Bibliotheca Latinitatis Mediaevalis (circa VII sec. - XIV sec. IntraText Digital Library [01/06] Corpus Scriptorum Latinorum. A digital library of Latin literature by David Camden [01/06] Fonti disponibili online concernenti la vita religiosa medievale Rete Vitae Religiosae Mediaevalis Studia Conectens [01/06] Fuentes del Medievo Hispanico Instituto de Historia, Consejo Superior de Investigaciones Científicas [01/06] Latin Literature Forum Romanum [01/06] Ludovico Antonio Muratori, Dissertazioni sopra le antichità italiane, 1751 Biblioteca dei Classici Italiani di Giuseppe Bonghi [01/06] Medieval Latin The Latin Library [01/06] Médiévales Presses Universitaires de Vincennes - Revues.org [01/06] Regesta imperii Deutsche Kommission für die Bearbeitung der Regesta Imperii e.V. [01/06] Suda On Line Byzantine Lexicography [01/06

  1. Digital mammography, cancer screening: Factors important for image compression

    Science.gov (United States)

    Clarke, Laurence P.; Blaine, G. James; Doi, Kunio; Yaffe, Martin J.; Shtern, Faina; Brown, G. Stephen; Winfield, Daniel L.; Kallergi, Maria

    1993-01-01

    The use of digital mammography for breast cancer screening poses several novel problems such as development of digital sensors, computer assisted diagnosis (CAD) methods for image noise suppression, enhancement, and pattern recognition, compression algorithms for image storage, transmission, and remote diagnosis. X-ray digital mammography using novel direct digital detection schemes or film digitizers results in large data sets and, therefore, image compression methods will play a significant role in the image processing and analysis by CAD techniques. In view of the extensive compression required, the relative merit of 'virtually lossless' versus lossy methods should be determined. A brief overview is presented here of the developments of digital sensors, CAD, and compression methods currently proposed and tested for mammography. The objective of the NCI/NASA Working Group on Digital Mammography is to stimulate the interest of the image processing and compression scientific community for this medical application and identify possible dual use technologies within the NASA centers.

  2. Probabilistic Open Set Recognition

    Science.gov (United States)

    Jain, Lalit Prithviraj

    Real-world tasks in computer vision, pattern recognition and machine learning often touch upon the open set recognition problem: multi-class recognition with incomplete knowledge of the world and many unknown inputs. An obvious way to approach such problems is to develop a recognition system that thresholds probabilities to reject unknown classes. Traditional rejection techniques are not about the unknown; they are about the uncertain boundary and rejection around that boundary. Thus traditional techniques only represent the "known unknowns". However, a proper open set recognition algorithm is needed to reduce the risk from the "unknown unknowns". This dissertation examines this concept and finds existing probabilistic multi-class recognition approaches are ineffective for true open set recognition. We hypothesize the cause is due to weak adhoc assumptions combined with closed-world assumptions made by existing calibration techniques. Intuitively, if we could accurately model just the positive data for any known class without overfitting, we could reject the large set of unknown classes even under this assumption of incomplete class knowledge. For this, we formulate the problem as one of modeling positive training data by invoking statistical extreme value theory (EVT) near the decision boundary of positive data with respect to negative data. We provide a new algorithm called the PI-SVM for estimating the unnormalized posterior probability of class inclusion. This dissertation also introduces a new open set recognition model called Compact Abating Probability (CAP), where the probability of class membership decreases in value (abates) as points move from known data toward open space. We show that CAP models improve open set recognition for multiple algorithms. Leveraging the CAP formulation, we go on to describe the novel Weibull-calibrated SVM (W-SVM) algorithm, which combines the useful properties of statistical EVT for score calibration with one-class and binary

  3. Digital Practice as Meaning Making in Archaeology

    Directory of Open Access Journals (Sweden)

    Gareth Beale

    2017-06-01

    Full Text Available Digital technologies and concepts of creativity have both been catalysts for great innovation in archaeology. However, the way in which this innovation has been understood and represented within archaeological discourse has been very different. The interplay between computing and archaeology has been less explicitly theoretical and less discursive than the interplay between the arts and archaeology. Largely lacking from this discourse, however, has been a recognition of the emergence of traditions of practice that are distinctly digital but which are rooted in archaeological epistemologies or, in other words, the development of a digital archaeological praxis. This themed issue of Internet Archaeology was conceived in order to allow archaeologists to explore these emerging traditions and to reflect upon their own digital practice.

  4. Touchless palmprint recognition systems

    CERN Document Server

    Genovese, Angelo; Scotti, Fabio

    2014-01-01

    This book examines the context, motivation and current status of biometric systems based on the palmprint, with a specific focus on touchless and less-constrained systems. It covers new technologies in this rapidly evolving field and is one of the first comprehensive books on palmprint recognition systems.It discusses the research literature and the most relevant industrial applications of palmprint biometrics, including the low-cost solutions based on webcams. The steps of biometric recognition are described in detail, including acquisition setups, algorithms, and evaluation procedures. Const

  5. FUNDAMENTALS OF SPEAKER RECOGNITION

    Directory of Open Access Journals (Sweden)

    Figen ERTAŞ

    2000-02-01

    Full Text Available The explosive growth of information technology in the last decade has made a considerable impact on the design and construction of systems for human-machine communication, which is becoming increasingly important in many aspects of life. Amongst other speech processing tasks, a great deal of attention has been devoted to developing procedures that identify people from their voices, and the design and construction of speaker recognition systems has been a fascinating enterprise pursued over many decades. This paper introduces speaker recognition in general and discusses its relevant parameters in relation to system performance.

  6. Digital Humanities and networked digital media

    DEFF Research Database (Denmark)

    Finnemann, Niels Ole

    2014-01-01

    This article discusses digital humanities and the growing diversity of digital media, digital materials and digital methods. The first section describes the humanities computing tradition formed around the interpretation of computation as a rule-based process connected to a concept of digital...... of software-supported methods. This is so, in part, because of the complexity of the world and, in part, because digital media remain open to the projection of new epistemologies onto the functional architecture of these media. The third section discusses the heterogeneous character of digital materials...

  7. Exhibits Recognition System for Combining Online Services and Offline Services

    Science.gov (United States)

    Ma, He; Liu, Jianbo; Zhang, Yuan; Wu, Xiaoyu

    2017-10-01

    In order to achieve a more convenient and accurate digital museum navigation, we have developed a real–time and online-to-offline museum exhibits recognition system using image recognition method based on deep learning. In this paper, the client and server of the system are separated and connected through the HTTP. Firstly, by using the client app in the Android mobile phone, the user can take pictures and upload them to the server. Secondly, the features of the picture are extracted using the deep learning network in the server. With the help of the features, the pictures user uploaded are classified with a well-trained SVM. Finally, the classification results are sent to the client and the detailed exhibition’s introduction corresponding to the classification results are shown in the client app. Experimental results demonstrate that the recognition accuracy is close to 100% and the computing time from the image uploading to the exhibit information show is less than 1S. By means of exhibition image recognition algorithm, our implemented exhibits recognition system can combine online detailed exhibition information to the user in the offline exhibition hall so as to achieve better digital navigation.

  8. [Prosopagnosia and facial expression recognition].

    Science.gov (United States)

    Koyama, Shinichi

    2014-04-01

    This paper reviews clinical neuropsychological studies that have indicated that the recognition of a person's identity and the recognition of facial expressions are processed by different cortical and subcortical areas of the brain. The fusiform gyrus, especially the right fusiform gyrus, plays an important role in the recognition of identity. The superior temporal sulcus, amygdala, and medial frontal cortex play important roles in facial-expression recognition. Both facial recognition and facial-expression recognition are highly intellectual processes that involve several regions of the brain.

  9. Recognition of Bullet Holes Based on Video Image Analysis

    Science.gov (United States)

    Ruolin, Zhu; Jianbo, Liu; Yuan, Zhang; Xiaoyu, Wu

    2017-10-01

    The technology of computer vision is used in the training of military shooting. In order to overcome the limitation of the bullet holes recognition using Video Image Analysis that exists over-detection or leak-detection, this paper adopts the support vector machine algorithm and convolutional neural network to extract and recognize Bullet Holes in the digital video and compares their performance. It extracts HOG characteristics of bullet holes and train SVM classifier quickly, though the target is under outdoor environment. Experiments show that support vector machine algorithm used in this paper realize a fast and efficient extraction and recognition of bullet holes, improving the efficiency of shooting training.

  10. Digital radiography

    DEFF Research Database (Denmark)

    Precht, H; Gerke, O; Rosendahl, K

    2012-01-01

    BACKGROUND: New developments in processing of digital radiographs (DR), including multi-frequency processing (MFP), allow optimization of image quality and radiation dose. This is particularly promising in children as they are believed to be more sensitive to ionizing radiation than adults...... image processing parameters, a significant dose reduction is possible without significant loss of image quality........ OBJECTIVE: To examine whether the use of MFP software reduces the radiation dose without compromising quality at DR of the femur in 5-year-old-equivalent anthropomorphic and technical phantoms. MATERIALS AND METHODS: A total of 110 images of an anthropomorphic phantom were imaged on a DR system (Canon DR...

  11. Digital pathology

    CERN Document Server

    Sucaet, Yves

    2014-01-01

    Digital pathology has experienced exponential growth, in terms of its technology and applications, since its inception just over a decade ago. Though it has yet to be approved for primary diagnostics, its values as a teaching tool, facilitator of second opinions and quality assurance reviews and research are becoming, if not already, undeniable. It also offers the hope of providing pathology consultant and educational services to under-served areas, including regions of the world that could not possibly sustain this level of services otherwise. And this is just the beginning, as its adoption b

  12. Harmonization versus Mutual Recognition

    DEFF Research Database (Denmark)

    Jørgensen, Jan Guldager; Schröder, Philipp

    The present paper examines trade liberalization driven by the coordination of product standards. For oligopolistic firms situated in separate markets that are initially sheltered by national standards, mutual recognition of standards implies entry and reduced profits at home paired with the oppor...

  13. Facial Expression Recognition

    NARCIS (Netherlands)

    Pantic, Maja; Li, S.; Jain, A.

    2009-01-01

    Facial expression recognition is a process performed by humans or computers, which consists of: 1. Locating faces in the scene (e.g., in an image; this step is also referred to as face detection), 2. Extracting facial features from the detected face region (e.g., detecting the shape of facial

  14. Recognition of fractal graphs

    NARCIS (Netherlands)

    Perepelitsa, VA; Sergienko, [No Value; Kochkarov, AM

    1999-01-01

    Definitions of prefractal and fractal graphs are introduced, and they are used to formulate mathematical models in different fields of knowledge. The topicality of fractal-graph recognition from the point of view, of fundamental improvement in the efficiency of the solution of algorithmic problems

  15. A Leaf Recognition Of Vegetables Using Matlab

    Directory of Open Access Journals (Sweden)

    Nadine Jaan D. Caldito

    2015-08-01

    Full Text Available Recognizing plants is a vital problem especially for biologists agricultural researchers and environmentalists. Plant recognition can be performed by human experts manually but it is a time consuming and low-efficiency process. Automation of plant recognition is an important process for the fields working with plants. This paper presents an approach for plant recognition using leaf images. In this study the proponents demonstrated the development of the system that gives users the ability to identify vegetables based on photographs of the leaves taken with a high definition camera. At the heart of this system is a modernize process of identification so as to automate the way of identifying the vegetable plants through leaf image and digital image processing. The system used the Gabor Filter Edge Detection RGB Color and Grayscale Image to acquire the physical parameter of the leaves. The output parameters are used to compute well documented metrics for the statistical and shape. Base on the study the following conclusion are drawn The system can extract the physical parameters from the leafs image that will be used in identifying Vegetables. From the extracted leaf parameters the system provides the statistical analysis and general information of the identified leaf. The used algorithm can organize data and information to useful resources to the future researchers.

  16. Connected digit speech recognition system for Malayalam language

    Indian Academy of Sciences (India)

    Department of Computer Applications, Cochin University of Science & Technology,. Cochin 682 022, India ... group of 20 to 40 years and the sound is recorded in the normal office environment where each speaker ... ture the signal, channels used to transmit the signal and even the environment too can change the signals.

  17. A Novel Optical/digital Processing System for Pattern Recognition

    Science.gov (United States)

    Boone, Bradley G.; Shukla, Oodaye B.

    1993-01-01

    This paper describes two processing algorithms that can be implemented optically: the Radon transform and angular correlation. These two algorithms can be combined in one optical processor to extract all the basic geometric and amplitude features from objects embedded in video imagery. We show that the internal amplitude structure of objects is recovered by the Radon transform, which is a well-known result, but, in addition, we show simulation results that calculate angular correlation, a simple but unique algorithm that extracts object boundaries from suitably threshold images from which length, width, area, aspect ratio, and orientation can be derived. In addition to circumventing scale and rotation distortions, these simulations indicate that the features derived from the angular correlation algorithm are relatively insensitive to tracking shifts and image noise. Some optical architecture concepts, including one based on micro-optical lenslet arrays, have been developed to implement these algorithms. Simulation test and evaluation using simple synthetic object data will be described, including results of a study that uses object boundaries (derivable from angular correlation) to classify simple objects using a neural network.

  18. Novel Tool for Complete Digitization of Paper Electrocardiography Data.

    Science.gov (United States)

    Ravichandran, Lakshminarayan; Harless, Chris; Shah, Amit J; Wick, Carson A; Mcclellan, James H; Tridandapani, Srini

    We present a Matlab-based tool to convert electrocardiography (ECG) information from paper charts into digital ECG signals. The tool can be used for long-term retrospective studies of cardiac patients to study the evolving features with prognostic value. To perform the conversion, we: 1) detect the graphical grid on ECG charts using grayscale thresholding; 2) digitize the ECG signal based on its contour using a column-wise pixel scan; and 3) use template-based optical character recognition to extract patient demographic information from the paper ECG in order to interface the data with the patients' medical record. To validate the digitization technique: 1) correlation between the digital signals and signals digitized from paper ECG are performed and 2) clinically significant ECG parameters are measured and compared from both the paper-based ECG signals and the digitized ECG. The validation demonstrates a correlation value of 0.85-0.9 between the digital ECG signal and the signal digitized from the paper ECG. There is a high correlation in the clinical parameters between the ECG information from the paper charts and digitized signal, with intra-observer and inter-observer correlations of 0.8-0.9 (p digitization tool to carry out retrospective studies on large databases, which rely on paper ECG records, studies of emerging ECG features can be performed. In addition, this tool can be used to potentially integrate digitized ECG information with digital ECG analysis programs and with the patient's electronic medical record.

  19. Autonomy and Recognition

    Directory of Open Access Journals (Sweden)

    Miguel Giusti

    2007-04-01

    Full Text Available Resumen:El presente ensayo contiene dos partes. En la primera se hace una breve descripción de las carencias de la reflexión moral a las que parece venir al encuentro el concepto de reconocimiento. Charles Taylor y Axel Honneth, protagonistas en estos debates, dan buenas razones para dirigir la discusión hacia el tema del reconocimiento, pero no coinciden ni en su definición, ni en el modo de recuperar la tesis de Hegel, ni tampoco en la forma de tratar la relación entre autonomía y reconocimiento. En la segunda parte se analiza la concepción propiamente hegeliana, con la intención de destacar el nexo esencial, no la ruptura, que existe entre la noción de reconocimiento y el modelo conceptual de la voluntad libre o del espíritu. Abstract:This essay is divided into two parts. The first one is a short description of the deficiencies of moral reflection, which seem to lead the discussion towards the concept of recognition. Charles Taylor and Axel Honneth, two of the protagonists of these debates, give very good reasons for turning the argument towards the issue of recognition, but they do not agree on its definition, on the way to recover the Hegelian thesis, or on how to approach the relationship between autonomy and recognition. The second part constitutes an analysis of the Hegelian conception of recognition, in order to highlight the essential link –rather than the rupture– between the notion of recognition and the conceptual model of free will or spirit.

  20. Digital Humanities

    DEFF Research Database (Denmark)

    Nielsen, Hans Jørn

    2015-01-01

    overgangen fra trykkekultur til digital kultur. For det første problemstillingen omkring digitalisering af litterær kulturarv med fokus på kodning og tagging af teksten samt organisering i hypertekststrukturer. For det andet reorganiseringen af det digitale dokument i dataelementer og database. For det......Artiklen præsenterer først nogle generelle problemstillinger omkring Digital Humanities (DH) med det formål at undersøge dem nærmere i relation til konkrete eksempler på forskellige digitaliseringsmåder og ændringer i dokumentproduktion. I en nærmere afgrænsning vælger artiklen den tendens i DH......, der betragter DH som forbundet med "making" og "building" af digitale objekter og former. Dette kan også karakteriseres som DH som praktisk-produktiv vending. Artiklen har valgt tre typer af digitalisering. De er valgt ud fra, at de skal repræsentere forskellige måder at håndtere digitaliseringen på...

  1. Stereotype Associations and Emotion Recognition

    NARCIS (Netherlands)

    Bijlstra, Gijsbert; Holland, Rob W.; Dotsch, Ron; Hugenberg, Kurt; Wigboldus, Daniel H. J.

    We investigated whether stereotype associations between specific emotional expressions and social categories underlie stereotypic emotion recognition biases. Across two studies, we replicated previously documented stereotype biases in emotion recognition using both dynamic (Study 1) and static

  2. Galeotti on recognition as inclusion

    DEFF Research Database (Denmark)

    Lægaard, Sune

    2008-01-01

    Anna Elisabetta Galeotti's theory of 'toleration as recognition' has been criticised by Peter Jones for being conceptually incoherent, since liberal toleration presupposes a negative attitude to differences, whereas multicultural recognition requires positive affirmation hereof. The paper spells ...

  3. Learner autonomy development through digital gameplay

    Directory of Open Access Journals (Sweden)

    Alice Chik

    2011-04-01

    Full Text Available Playing digital games is undeniably a popular leisure activity, and digital gaming is also gaining academic attention and recognition for enhancing digital literacies and learning motivation. One tricky issue when exploring digital gaming in Asian contexts is the popularity of English and Japanese games. Though Chinese and Korean online games are readily available, many of the more popular commercial off-the-shelf (COTS digital games are in English and Japanese. Students in Hong Kong are required to take English as a foreign language, which resulted in a huge range of proficiency, but Japanese is not offered at public schools. So, most Hong Kong gamers are playing foreign language games. Yet language barriers do not diminish the market demand for foreign language digital games. This paper explores the phenomenon of digital gaming in foreign languages. Based on findings from an on-going research project with ten undergraduate video gamers (F=4, M=6, this paper argues that gamers exercise learner autonomy by managing their gaming both as leisure and learning experiences.

  4. Doing Justice to Recognition

    Directory of Open Access Journals (Sweden)

    Will Colish

    2009-06-01

    Full Text Available The traditional role of justice is to arbitrate where the good will of people is not enough, if even present, to settle a dispute between the concerned parties. It is a procedural approach that assumes a fractured relationship between those involved. Recognition, at first glance, would not seem to mirror these aspects of justice. Yet recognition is very much a subject of justice these days. The aim of this paper is to question the applicability of justice to the practice of recognition. The methodological orientation of this paper is a Kantian-style critique of the institution of justice, highlighting the limits of its reach and the dangers of overextension. The critique unfolds in the following three steps: 1 There is an immediate appeal to justice as a practice of recognition through its commitment to universality. This allure is shown to be deceptive in providing no prescription for the actual practice of this universality. 2 The interventionist character of justice is designed to address divided relationships. If recognition is only given expression through this channel, then we can only assume division as our starting ground. 3 The outcome of justice in respect to recognition is identification. This identification is left vulnerable to misrecognition itself, creating a cycle of injustice that demands recognition from anew. It seems to be well accepted that recognition is essentjustice, but less clear how to do justice to recognition. This paper is an effort in clarification. Le rôle traditionnel de la justice est celui d’arbitrer des situations où la bonne volonté ne suffit pas à régler un différend entre les parties concernées. Il s'agit d'une approche procédurale qui suppose une relation brisée entre les personnes impliquées. La reconnaissance, à première vue, ne semble pas refléter ces caractéristiques de la justice. Pourtant, elle est souvent présentée comme rétablissant une justice entre les parties concernés. Le

  5. Immediate recognition memory for wine

    OpenAIRE

    Johnson, A.J.; Volp, A.; Miles, C.

    2014-01-01

    We describe a preliminary investigation concerning the short-term recognition memory function for gustatory stimuli (wines). In Experiment 1a, 24 non-expert wine drinkers completed a yes/no recognition task for 3-wine sequences. For the raw recognition scores, the serial position function comprised both primacy and recency. Recency did not, however, achieve significance for the d′ scores. In Experiment 1b, 24 participants completed the same yes/no recognition task for 3-visual matrix sequence...

  6. Fuzzy logic and neural networks in artificial intelligence and pattern recognition

    Science.gov (United States)

    Sanchez, Elie

    1991-10-01

    With the use of fuzzy logic techniques, neural computing can be integrated in symbolic reasoning to solve complex real world problems. In fact, artificial neural networks, expert systems, and fuzzy logic systems, in the context of approximate reasoning, share common features and techniques. A model of Fuzzy Connectionist Expert System is introduced, in which an artificial neural network is designed to construct the knowledge base of an expert system from, training examples (this model can also be used for specifications of rules in fuzzy logic control). Two types of weights are associated with the synaptic connections in an AND-OR structure: primary linguistic weights, interpreted as labels of fuzzy sets, and secondary numerical weights. Cell activation is computed through min-max fuzzy equations of the weights. Learning consists in finding the (numerical) weights and the network topology. This feedforward network is described and first illustrated in a biomedical application (medical diagnosis assistance from inflammatory-syndromes/proteins profiles). Then, it is shown how this methodology can be utilized for handwritten pattern recognition (characters play the role of diagnoses): in a fuzzy neuron describing a number for example, the linguistic weights represent fuzzy sets on cross-detecting lines and the numerical weights reflect the importance (or weakness) of connections between cross-detecting lines and characters.

  7. Forensic Face Recognition: A Survey

    NARCIS (Netherlands)

    Ali, Tauseef; Spreeuwers, Lieuwe Jan; Veldhuis, Raymond N.J.; Quaglia, Adamo; Epifano, Calogera M.

    2012-01-01

    The improvements of automatic face recognition during the last 2 decades have disclosed new applications like border control and camera surveillance. A new application field is forensic face recognition. Traditionally, face recognition by human experts has been used in forensics, but now there is a

  8. Visual Recognition Memory across Contexts

    Science.gov (United States)

    Jones, Emily J. H.; Pascalis, Olivier; Eacott, Madeline J.; Herbert, Jane S.

    2011-01-01

    In two experiments, we investigated the development of representational flexibility in visual recognition memory during infancy using the Visual Paired Comparison (VPC) task. In Experiment 1, 6- and 9-month-old infants exhibited recognition when familiarization and test occurred in the same room, but showed no evidence of recognition when…

  9. Image recognition: visual grouping, recognition, and learning.

    Science.gov (United States)

    Buhmann, J M; Malik, J; Perona, P

    1999-12-07

    Vision extracts useful information from images. Reconstructing the three-dimensional structure of our environment and recognizing the objects that populate it are among the most important functions of our visual system. Computer vision researchers study the computational principles of vision and aim at designing algorithms that reproduce these functions. Vision is difficult: the same scene may give rise to very different images depending on illumination and viewpoint. Typically, an astronomical number of hypotheses exist that in principle have to be analyzed to infer a correct scene description. Moreover, image information might be extracted at different levels of spatial and logical resolution dependent on the image processing task. Knowledge of the world allows the visual system to limit the amount of ambiguity and to greatly simplify visual computations. We discuss how simple properties of the world are captured by the Gestalt rules of grouping, how the visual system may learn and organize models of objects for recognition, and how one may control the complexity of the description that the visual system computes.

  10. Method of synthesized phase objects for pattern recognition: matched filtering.

    Science.gov (United States)

    Yezhov, Pavel V; Kuzmenko, Alexander V; Kim, Jin-Tae; Smirnova, Tatiana N

    2012-12-31

    To solve the pattern recognition problem, a method of synthesized phase objects is suggested. The essence of the suggested method is that synthesized phase objects are used instead of real amplitude objects. The former is object-dependent phase distributions calculated using the iterative Fourier-transform (IFT) algorithm. The method is experimentally studied with a Vander Lugt optical-digital 4F-correlator. We present the comparative analysis of recognition results using conventional and proposed methods, estimate the sensitivity of the latter to distortions of the structure of objects, and determine the applicability limits. It is demonstrated that the proposed method allows one: (а) to simplify the procedure of choice of recognition signs (criteria); (b) to obtain one-type δ-like recognition signals irrespective of the type of objects; (с) to improve signal-to-noise ratio (SNR) for correlation signals by 20 - 30 dB on average. The spatial separation of the Fourier-spectra of objects and optical noises of the correlator by means of the superposition of the phase grating on recognition objects at the recording of holographic filters and at the matched filtering has additionally improved SNR (>10 dB) for correlation signals. To introduce recognition objects in the correlator, we use a SLM LC-R 2500 device. Matched filters are recorded on a self-developing photopolymer.

  11. Focus: Digital

    DEFF Research Database (Denmark)

    Technology has been an all-important and defining element within the arts throughout the 20th century, and it has fundamentally changed the ways in which we produce and consume music. With this Focus we investigate the latest developments in the digital domain – and their pervasiveness and rapid...... production and reception of contemporary music and sound art. With ‘Digital’ we present four composers' very different answers to how technology impact their work. To Juliana Hodkinson it has become an integral part of her sonic writing. Rudiger Meyer analyses the relationships between art and design and how...... pace, which demand a closer look at the relations between arts and technology. The composers’ understanding of her occupation is challenged – and alongside, mediatisation and changes in distribution mark an incursion on solid conceptions of the artwork. Together, this means changing conditions for both...

  12. Fokus: Digital

    DEFF Research Database (Denmark)

    2014-01-01

    i det digitale domæne – udviklinger, der foregår hastigt og er gennemgribende, og som derfor kræver et nærmere blik på forholdet mellem kunsten og teknologien. Komponistens forståelse af sin metier udfordres – samtidig med at befæstede ideer om kunstværket møder modstand fra nye mediemæssige...... sammenhænge og fra forandrede distributionsformer. Dette betyder ændrede betingelser for både produktion og reception af kunstmusik og lydkunst. Med Digital tager vi udgangspunkt i fire komponisters meget forskellige bud på hvordan teknologien spiller en rolle i arbejdet. Juliana Hodkinson beskriver hvordan...

  13. Digital entrepreneurship

    DEFF Research Database (Denmark)

    Brem, Alexander; Richter, Chris; Kraus, Sascha

    2017-01-01

    What's mine is yours. An increasing number of people are participating in sharing and exchanging information, knowledge, data and goods. As research addressing the so-called ‘sharing economy’ is still in its infancy, this article aims to shed light on it. To do this, a qualitative research approach...... comprising guided interviews with 14 companies from Germany, Austria and Switzerland provides detailed insights into different aspects of the sharing economy phenomenon. Our results make a direct contribution to sharing economy research, especially regarding the new business models of start-ups. Here, we...... find a clear difference between the relevance of economic and social orientation. The latter appears to be in higher demand among customers than entrepreneurs. The increasingly digitalized environment has led to a changed living situation characterized by urbanity, openness to new solutions, changed...

  14. Towards Automatic Threat Recognition

    Science.gov (United States)

    2006-12-01

    York: Bantam. Forschungsinstitut für Kommunikation , Informationsverarbeitung und Ergonomie FGAN Informationstechnik und Führungssysteme KIE Towards...Automatic Threat Recognition Dr. Ulrich Schade Joachim Biermann Miłosław Frey FGAN – FKIE Germany Forschungsinstitut für Kommunikation ...as Processing Principle Back to the Example Conclusion and Outlook Forschungsinstitut für Kommunikation , Informationsverarbeitung und Ergonomie FGAN

  15. Amazigh recognition in Algeria

    OpenAIRE

    Kristensen, Mia; Meškinytė, Vilma

    2015-01-01

    The indigenous people of North Africa, the Amazigh population, have been outnumbered by the Arabs since their invasion in the 7th century. Fighting and bombing heads have been regular ever since. However, during the period of decolonization the two populations fought side by side. After independence in the North African countries a heavy Arabisation followed, once again creating tension between the Arab and Amazigh population. Fighting to get recognition the Amazigh population has gained some...

  16. Pattern Recognition Control Design

    Science.gov (United States)

    Gambone, Elisabeth A.

    2018-01-01

    Spacecraft control algorithms must know the expected vehicle response to any command to the available control effectors, such as reaction thrusters or torque devices. Spacecraft control system design approaches have traditionally relied on the estimated vehicle mass properties to determine the desired force and moment, as well as knowledge of the effector performance to efficiently control the spacecraft. A pattern recognition approach was used to investigate the relationship between the control effector commands and spacecraft responses. Instead of supplying the approximated vehicle properties and the thruster performance characteristics, a database of information relating the thruster ring commands and the desired vehicle response was used for closed-loop control. A Monte Carlo simulation data set of the spacecraft dynamic response to effector commands was analyzed to establish the influence a command has on the behavior of the spacecraft. A tool developed at NASA Johnson Space Center to analyze flight dynamics Monte Carlo data sets through pattern recognition methods was used to perform this analysis. Once a comprehensive data set relating spacecraft responses with commands was established, it was used in place of traditional control methods and gains set. This pattern recognition approach was compared with traditional control algorithms to determine the potential benefits and uses.

  17. [Handwritten documents of 'Antidotarius magnus'].

    Science.gov (United States)

    Kramer, A; Scheidt, K

    1999-01-01

    The 'Antidotarius magnus'--compiled about 1080 by the archbishop of Salerno, Alphanus--deals with the pharmacological methods of healing and contains nearly 1073 antidots. We have discovered 13 Latin manuscripts of the 'Antidotarius magnus' in the libraries of Basel, Bern, Cambridge, Erfurt, Florence, London, Oxford, Paris and Parma. One should remember that the MS Taurin.I.VI.24 had been totally destroyed in 1904, but this manuscript is still noted in the catalogues of Pasin, Giacosa and Thorndike/Kibre. The most remarkable manuscript--the MS Palat.lat.747--is preserved in the National Library at Florence. The MS Palat.lat.747 is dated to 1153 and seems to be similar to the archetype. We are currently preparing a critical edition based on the oldest manuscripts.

  18. Audio-visual gender recognition

    Science.gov (United States)

    Liu, Ming; Xu, Xun; Huang, Thomas S.

    2007-11-01

    Combining different modalities for pattern recognition task is a very promising field. Basically, human always fuse information from different modalities to recognize object and perform inference, etc. Audio-Visual gender recognition is one of the most common task in human social communication. Human can identify the gender by facial appearance, by speech and also by body gait. Indeed, human gender recognition is a multi-modal data acquisition and processing procedure. However, computational multimodal gender recognition has not been extensively investigated in the literature. In this paper, speech and facial image are fused to perform a mutli-modal gender recognition for exploring the improvement of combining different modalities.

  19. Clustering algorithms for Stokes space modulation format recognition

    DEFF Research Database (Denmark)

    Boada, Ricard; Borkowski, Robert; Tafur Monroy, Idelfonso

    2015-01-01

    Stokes space modulation format recognition (Stokes MFR) is a blind method enabling digital coherent receivers to infer modulation format information directly from a received polarization-division-multiplexed signal. A crucial part of the Stokes MFR is a clustering algorithm, which largely...... for discriminating between dual polarization: BPSK, QPSK, 8-PSK, 8-QAM, and 16-QAM. We determine essential performance metrics for each clustering algorithm and modulation format under test: minimum required signal-to-noise ratio, detection accuracy and algorithm complexity....

  20. USNA DIGITAL FORENSICS LAB

    Data.gov (United States)

    Federal Laboratory Consortium — To enable Digital Forensics and Computer Security research and educational opportunities across majors and departments. Lab MissionEstablish and maintain a Digital...

  1. Journal of digital information

    National Research Council Canada - National Science Library

    1990-01-01

    Contains articles, book reviews and lab reports dealing with digital libraries, hypermedia systems, intelligent agents, information management, interfaces to digital information, social consequences...

  2. Can We Teach Digital Natives Digital Literacy?

    Science.gov (United States)

    Ng, Wan

    2012-01-01

    In recent years, there has been much debate about the concept of digital natives, in particular the differences between the digital natives' knowledge and adoption of digital technologies in informal versus formal educational contexts. This paper investigates the knowledge about educational technologies of a group of undergraduate students…

  3. A Malaysian Vehicle License Plate Localization and Recognition System

    Directory of Open Access Journals (Sweden)

    Ganapathy Velappa

    2008-02-01

    Full Text Available Technological intelligence is a highly sought after commodity even in traffic-based systems. These intelligent systems do not only help in traffic monitoring but also in commuter safety, law enforcement and commercial applications. In this paper, a license plate localization and recognition system for vehicles in Malaysia is proposed. This system is developed based on digital images and can be easily applied to commercial car park systems for the use of documenting access of parking services, secure usage of parking houses and also to prevent car theft issues. The proposed license plate localization algorithm is based on a combination of morphological processes with a modified Hough Transform approach and the recognition of the license plates is achieved by the implementation of the feed-forward backpropagation artificial neural network. Experimental results show an average of 95% successful license plate localization and recognition in a total of 589 images captured from a complex outdoor environment.

  4. Automatic Radiographic Position Recognition from Image Frequency and Intensity

    Directory of Open Access Journals (Sweden)

    Ning-ning Ren

    2017-01-01

    Full Text Available Purpose. With the development of digital X-ray imaging and processing methods, the categorization and analysis of massive digital radiographic images need to be automatically finished. What is crucial in this processing is the automatic retrieval and recognition of radiographic position. To address these concerns, we developed an automatic method to identify a patient’s position and body region using only frequency curve classification and gray matching. Methods. Our new method is combined with frequency analysis and gray image matching. The radiographic position was determined from frequency similarity and amplitude classification. The body region recognition was performed by image matching in the whole-body phantom image with prior knowledge of templates. The whole-body phantom image was stitched by radiological images of different parts. Results. The proposed method can automatically retrieve and recognize the radiographic position and body region using frequency and intensity information. It replaces 2D image retrieval with 1D frequency curve classification, with higher speed and accuracy up to 93.78%. Conclusion. The proposed method is able to outperform the digital X-ray image’s position recognition with a limited time cost and a simple algorithm. The frequency information of radiography can make image classification quicker and more accurate.

  5. Digital forensics digital evidence in criminal investigations

    CERN Document Server

    Marshall, Angus McKenzie

    2009-01-01

    The vast majority of modern criminal investigations involve some element of digital evidence, from mobile phones, computers, CCTV and other devices. Digital Forensics: Digital Evidence in Criminal Investigations provides the reader with a better understanding of how digital evidence complements "traditional" scientific evidence and examines how it can be used more effectively and efficiently in a range of investigations. Taking a new approach to the topic, this book presents digital evidence as an adjunct to other types of evidence and discusses how it can be deployed effectively in s

  6. Digital dannelse

    DEFF Research Database (Denmark)

    Bundsgaard, Jeppe

    2012-01-01

    I al vores iver efter at få presset nogle flere digitale dimser ind i skolen, er vi i fare for at glemme hvad det er vi skal med disse dimser. Der er store forventninger til at de kan gøre det lettere at være lærer (og dermed billigere), og det kan det måske. Men der er jo også et dannelsesspørgs......I al vores iver efter at få presset nogle flere digitale dimser ind i skolen, er vi i fare for at glemme hvad det er vi skal med disse dimser. Der er store forventninger til at de kan gøre det lettere at være lærer (og dermed billigere), og det kan det måske. Men der er jo også et...... dannelsesspørgsmål knyttet til it. Hvad er egentlig digital dannelse? Og hvad betyder det for danskfaget?...

  7. Digital produktion

    DEFF Research Database (Denmark)

    Bogen sætter fokus på digital produktion, som er en stærk læringsform, der faciliterer elevernes læreprocesser og kvalificerer elevernes faglige læringsresultater. Det sker når lærerne udarbejder didaktiske rammedesign, hvor eleverne arbejder selvstændigt inden for dette rammedesign, og hvor mål og...... procesevaluering stilladserer elevernes faglige proces. I digitale produktionsprocesser arbejder eleverne iterativt, de udvikler ejerskab til produktionen og fastholder selv deres læreprocesser. It’s multimodalitet, elevernes kollaborative tilgange, videndeling mellem eleverne og elevernes uformelle lege- og...... elevernes digitale produktion er lærernes didaktiske rammesætning og stilladserende tilgange. Her lægger lærerne op til, at eleverne som didaktiske designere i relation til rammesætningen skal organisere og planlægge deres læreprocesser, inddrages i målsætning, evaluering og valg af digitale ressourcer...

  8. Digital Copies and Digital Museums in a Digital Cultural Policy

    Directory of Open Access Journals (Sweden)

    Ole Marius Hylland

    2017-09-01

    Full Text Available This article investigates how a digital turn and digital copies have influenced ideas, roles and authorities within a national museum sector. It asks whether digital mu-seums and their digital reproductions expand and/or challenge a traditional cul-tural policy. Two specific cases are highlighted to inform the discussion on these questions - the Norwegian digital museum platform DigitaltMuseum and Google Art Project. The article argues that there is a certain epochalism at play when the impact of a digital turn is analysed. At the same time, some clear major changes are taking place, even if their impact on cultural policies might be less than expec-ted. I propose that one of the changes is the replacing of authenticity with accessi-bility as the primary legitimating value of museum objects.

  9. Digital platforms as enablers for digital transformation

    DEFF Research Database (Denmark)

    Hossain, Mokter; Lassen, Astrid Heidemann

    transformation is crucial. This study aims at exploring how organizations are driven towards transformation in various ways to embrace digital platforms for ideas, technologies, and knowledge. It shows the opportunities and challenges digital platforms bring in organizations. It also highlights underlying......Digital platforms offer new ways for organizations to collaborate with the external environment for ideas, technologies, and knowledge. They provide new possibilities and competence but they also bring new challenges for organizations. Understanding the role of these platforms in digital...... mechanisms and potential outcomes of various digital platforms. The contribution of the submission is valuable for scholars to understand and further explore this area. It provides insight for practitioners to capture value through digital platforms and accelerate the pace of organizations’ digital...

  10. Re-thinking employee recognition: understanding employee experiences of recognition

    OpenAIRE

    Smith, Charlotte

    2013-01-01

    Despite widespread acceptance of the importance of employee recognition for both individuals and organisations and evidence of its increasing use in organisations, employee recognition has received relatively little focused attention from academic researchers. Particularly lacking is research exploring the lived experience of employee recognition and the interpretations and meanings which individuals give to these experiences. Drawing on qualitative interviews conducted as part of my PhD rese...

  11. Optical time-domain analog pattern correlator for high-speed real-time image recognition.

    Science.gov (United States)

    Kim, Sang Hyup; Goda, Keisuke; Fard, Ali; Jalali, Bahram

    2011-01-15

    The speed of image processing is limited by image acquisition circuitry. While optical pattern recognition techniques can reduce the computational burden on digital image processing, their image correlation rates are typically low due to the use of spatial optical elements. Here we report a method that overcomes this limitation and enables fast real-time analog image recognition at a record correlation rate of 36.7 MHz--1000 times higher rates than conventional methods. This technique seamlessly performs image acquisition, correlation, and signal integration all optically in the time domain before analog-to-digital conversion by virtue of optical space-to-time mapping.

  12. H. Sapiens Digital: From Digital Immigrants and Digital Natives to Digital Wisdom

    Science.gov (United States)

    Prensky, Marc

    2009-01-01

    As we move further into the 21st century, the digital native/digital immigrant paradigm created by Marc Prensky in 2001 is becoming less relevant. In this article, Prensky suggests that we should focus instead on the development of what he calls "digital wisdom." Arguing that digital technology can make us not just smarter but truly wiser, Prensky…

  13. 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

  14. Bispectral methods of signal processing applications in radar, telecommunications and digital image restoration

    CERN Document Server

    Totsky, Alexander V; Kravchenko, Victor F

    2015-01-01

    By studying applications in radar, telecommunications and digital image restoration, this monograph discusses signal processing techniques based on bispectral methods. Improved robustness against different forms of noise as well as preservation of phase information render this method a valuable alternative to common power-spectrum analysis used in radar object recognition, digital wireless communications, and jitter removal in images.

  15. Inverse Scattering Approach to Improving Pattern Recognition

    Energy Technology Data Exchange (ETDEWEB)

    Chapline, G; Fu, C

    2005-02-15

    The Helmholtz machine provides what may be the best existing model for how the mammalian brain recognizes patterns. Based on the observation that the ''wake-sleep'' algorithm for training a Helmholtz machine is similar to the problem of finding the potential for a multi-channel Schrodinger equation, we propose that the construction of a Schrodinger potential using inverse scattering methods can serve as a model for how the mammalian brain learns to extract essential information from sensory data. In particular, inverse scattering theory provides a conceptual framework for imagining how one might use EEG and MEG observations of brain-waves together with sensory feedback to improve human learning and pattern recognition. Longer term, implementation of inverse scattering algorithms on a digital or optical computer could be a step towards mimicking the seamless information fusion of the mammalian brain.

  16. Inverse scattering approach to improving pattern recognition

    Science.gov (United States)

    Chapline, George; Fu, Chi-Yung

    2005-05-01

    The Helmholtz machine provides what may be the best existing model for how the mammalian brain recognizes patterns. Based on the observation that the "wake-sleep" algorithm for training a Helmholtz machine is similar to the problem of finding the potential for a multi-channel Schrodinger equation, we propose that the construction of a Schrodinger potential using inverse scattering methods can serve as a model for how the mammalian brain learns to extract essential information from sensory data. In particular, inverse scattering theory provides a conceptual framework for imagining how one might use EEG and MEG observations of brain-waves together with sensory feedback to improve human learning and pattern recognition. Longer term, implementation of inverse scattering algorithms on a digital or optical computer could be a step towards mimicking the seamless information fusion of the mammalian brain.

  17. Study on municipal road cracking and surface deformation based on image recognition

    Science.gov (United States)

    Yuan, Haitao; Wang, Shuai; Tan, Jizong

    2017-05-01

    In recent years, the digital image recognition technology of concrete structure cracks and deformation of binocular vision technology detection of civil engineering structure have made substantial development. As a result, people's understanding of the road engineering structure cracking and surface deformation recognition gives rise to a new situation. For the research on digital image concrete structure cracking and masonry structure surface deformation recognition technology, the key is to break through in the method, and to improve the traditional recognition technology and mode. Only in this way can we continuously improve the security level of the highway, to adapt to the new requirements of the development of new urbanization and modernization. This thesis focuses on and systematically analyzes the digital image road engineering structure cracking and key technologies of surface deformation recognition and its engineering applications. In addition, we change the concrete structure cracking and masonry structure surface deformation recognition pattern, and realize the breakthrough and innovation of the road structure safety testing means and methods.

  18. Enabling Digital Literacy

    DEFF Research Database (Denmark)

    Ryberg, Thomas; Georgsen, Marianne

    2010-01-01

    There are some tensions between high-level policy definitions of “digital literacy” and actual teaching practice. We need to find workable definitions of digital literacy; obtain a better understanding of what digital literacy might look like in practice; and identify pedagogical approaches, which...... support teachers in designing digital literacy learning. We suggest that frameworks such as Problem Based Learning (PBL) are approaches that enable digital literacy learning because they provide good settings for engaging with digital literacy. We illustrate this through analysis of a case. Furthermore......, these operate on a meso-level mediating between high-level concepts of digital literacy and classroom practice....

  19. Human activity recognition and prediction

    CERN Document Server

    2016-01-01

    This book provides a unique view of human activity recognition, especially fine-grained human activity structure learning, human-interaction recognition, RGB-D data based action recognition, temporal decomposition, and causality learning in unconstrained human activity videos. The techniques discussed give readers tools that provide a significant improvement over existing methodologies of video content understanding by taking advantage of activity recognition. It links multiple popular research fields in computer vision, machine learning, human-centered computing, human-computer interaction, image classification, and pattern recognition. In addition, the book includes several key chapters covering multiple emerging topics in the field. Contributed by top experts and practitioners, the chapters present key topics from different angles and blend both methodology and application, composing a solid overview of the human activity recognition techniques. .

  20. Radically enhanced molecular recognition

    KAUST Repository

    Trabolsi, Ali

    2009-12-17

    The tendency for viologen radical cations to dimerize has been harnessed to establish a recognition motif based on their ability to form extremely strong inclusion complexes with cyclobis(paraquat-p-phenylene) in its diradical dicationic redox state. This previously unreported complex involving three bipyridinium cation radicals increases the versatility of host-guest chemistry, extending its practice beyond the traditional reliance on neutral and charged guests and hosts. In particular, transporting the concept of radical dimerization into the field of mechanically interlocked molecules introduces a higher level of control within molecular switches and machines. Herein, we report that bistable and tristable [2]rotaxanes can be switched by altering electrochemical potentials. In a tristable [2]rotaxane composed of a cyclobis(paraquat-p-phenylene) ring and a dumbbell with tetrathiafulvalene, dioxynaphthalene and bipyridinium recognition sites, the position of the ring can be switched. On oxidation, it moves from the tetrathiafulvalene to the dioxynaphthalene, and on reduction, to the bipyridinium radical cation, provided the ring is also reduced simultaneously to the diradical dication. © 2010 Macmillan Publishers Limited. All rights reserved.

  1. Digital preservation for heritages

    CERN Document Server

    Lu, Dongming

    2011-01-01

    ""Digital Preservation for Heritages: Technologies and Applications"" provides a comprehensive and up-to-date coverage of digital technologies in the area of cultural heritage preservation, including digitalization, research aiding, conservation aiding, digital exhibition, and digital utilization. Processes, technical frameworks, key technologies, as well as typical systems and applications are discussed in the book. It is intended for researchers and students in the fields of computer science and technology, museology, and archaeology. Dr. Dongming Lu is a professor at College of Computer Sci

  2. Digital Sensor Technology

    Energy Technology Data Exchange (ETDEWEB)

    Ted Quinn; Jerry Mauck; Richard Bockhorst; Ken Thomas

    2013-07-01

    The nuclear industry has been slow to incorporate digital sensor technology into nuclear plant designs due to concerns with digital qualification issues. However, the benefits of digital sensor technology for nuclear plant instrumentation are substantial in terms of accuracy, reliability, availability, and maintainability. This report demonstrates these benefits in direct comparisons of digital and analog sensor applications. It also addresses the qualification issues that must be addressed in the application of digital sensor technology.

  3. Deep Learning For Smile Recognition

    OpenAIRE

    Glauner, Patrick O.

    2016-01-01

    Inspired by recent successes of deep learning in computer vision, we propose a novel application of deep convolutional neural networks to facial expression recognition, in particular smile recognition. A smile recognition test accuracy of 99.45% is achieved for the Denver Intensity of Spontaneous Facial Action (DISFA) database, significantly outperforming existing approaches based on hand-crafted features with accuracies ranging from 65.55% to 79.67%. The novelty of this approach includes a c...

  4. Research of speech recognition methods

    OpenAIRE

    Prokopovič, Valerij

    2005-01-01

    Two speech recognition methods: Dynamic Time Warping and Hidden Markov model based methods were investigated in this work To estimate efficiency of the methods, speaker dependent and speaker independent isolated word recognition experiments were performed. During experimental research it was determined that Dynamic Time Warping method is suitable only for speaker dependent speech recognition. Hidden Markov model based method is suitable for both – speaker dependent and speaker independent spe...

  5. Pilgrims Face Recognition Dataset -- HUFRD

    OpenAIRE

    Aly, Salah A.

    2012-01-01

    In this work, we define a new pilgrims face recognition dataset, called HUFRD dataset. The new developed dataset presents various pilgrims' images taken from outside the Holy Masjid El-Harram in Makkah during the 2011-2012 Hajj and Umrah seasons. Such dataset will be used to test our developed facial recognition and detection algorithms, as well as assess in the missing and found recognition system \\cite{crowdsensing}.

  6. Markov Models for Handwriting Recognition

    CERN Document Server

    Plotz, Thomas

    2011-01-01

    Since their first inception, automatic reading systems have evolved substantially, yet the recognition of handwriting remains an open research problem due to its substantial variation in appearance. With the introduction of Markovian models to the field, a promising modeling and recognition paradigm was established for automatic handwriting recognition. However, no standard procedures for building Markov model-based recognizers have yet been established. This text provides a comprehensive overview of the application of Markov models in the field of handwriting recognition, covering both hidden

  7. Molecular Mechanisms of Odor Recognition

    National Research Council Canada - National Science Library

    Anholt, Robert

    2000-01-01

    .... We characterized the transduction pathway for the recognition of pheromones in the vomeronasal organ and also characterized subpopulations of olfactory neurons expressing different axonal G proteins...

  8. Recognition of facial and musical emotions in Parkinson's disease.

    Science.gov (United States)

    Saenz, A; Doé de Maindreville, A; Henry, A; de Labbey, S; Bakchine, S; Ehrlé, N

    2013-03-01

    Patients with amygdala lesions were found to be impaired in recognizing the fear emotion both from face and from music. In patients with Parkinson's disease (PD), impairment in recognition of emotions from facial expressions was reported for disgust, fear, sadness and anger, but no studies had yet investigated this population for the recognition of emotions from both face and music. The ability to recognize basic universal emotions (fear, happiness and sadness) from both face and music was investigated in 24 medicated patients with PD and 24 healthy controls. The patient group was tested for language (verbal fluency tasks), memory (digit and spatial span), executive functions (Similarities and Picture Completion subtests of the WAIS III, Brixton and Stroop tests), visual attention (Bells test), and fulfilled self-assessment tests for anxiety and depression. Results showed that the PD group was significantly impaired for recognition of both fear and sadness emotions from facial expressions, whereas their performance in recognition of emotions from musical excerpts was not different from that of the control group. The scores of fear and sadness recognition from faces were neither correlated to scores in tests for executive and cognitive functions, nor to scores in self-assessment scales. We attributed the observed dissociation to the modality (visual vs. auditory) of presentation and to the ecological value of the musical stimuli that we used. We discuss the relevance of our findings for the care of patients with PD. © 2012 The Author(s) European Journal of Neurology © 2012 EFNS.

  9. Automatic processing, analysis, and recognition of images

    Science.gov (United States)

    Abrukov, Victor S.; Smirnov, Evgeniy V.; Ivanov, Dmitriy G.

    2004-11-01

    New approaches and computer codes (A&CC) for automatic processing, analysis and recognition of images are offered. The A&CC are based on presentation of object image as a collection of pixels of various colours and consecutive automatic painting of distinguished itself parts of the image. The A&CC have technical objectives centred on such direction as: 1) image processing, 2) image feature extraction, 3) image analysis and some others in any consistency and combination. The A&CC allows to obtain various geometrical and statistical parameters of object image and its parts. Additional possibilities of the A&CC usage deal with a usage of artificial neural networks technologies. We believe that A&CC can be used at creation of the systems of testing and control in a various field of industry and military applications (airborne imaging systems, tracking of moving objects), in medical diagnostics, at creation of new software for CCD, at industrial vision and creation of decision-making system, etc. The opportunities of the A&CC are tested at image analysis of model fires and plumes of the sprayed fluid, ensembles of particles, at a decoding of interferometric images, for digitization of paper diagrams of electrical signals, for recognition of the text, for elimination of a noise of the images, for filtration of the image, for analysis of the astronomical images and air photography, at detection of objects.

  10. 2nd International Symposium on Signal Processing and Intelligent Recognition Systems

    CERN Document Server

    Bandyopadhyay, Sanghamitra; Krishnan, Sri; Li, Kuan-Ching; Mosin, Sergey; Ma, Maode

    2016-01-01

    This Edited Volume contains a selection of refereed and revised papers originally presented at the second International Symposium on Signal Processing and Intelligent Recognition Systems (SIRS-2015), December 16-19, 2015, Trivandrum, India. The program committee received 175 submissions. Each paper was peer reviewed by at least three or more independent referees of the program committee and the 59 papers were finally selected. The papers offer stimulating insights into biometrics, digital watermarking, recognition systems, image and video processing, signal and speech processing, pattern recognition, machine learning and knowledge-based systems. The book is directed to the researchers and scientists engaged in various field of signal processing and related areas. .

  11. Development of a Digital Mapping Program at the Defense Mapping Agency.

    Science.gov (United States)

    1984-04-02

    operations is covered. Special emphasis is placed on the rationale for ieenaio of enhaced hardwar and software / technologies into the production...requirements at minimum cost. DMA is also investigating digital image processing in support of an all digital production system. Studies include...interactive feature extraction and applied pattern recognition and are carried out on a digital image processing test bed delivered to DMA in 1981. This test

  12. 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.

  13. Iris Recognition Using Wavelet

    Directory of Open Access Journals (Sweden)

    Khaliq Masood

    2013-08-01

    Full Text Available Biometric systems are getting more attention in the present era. Iris recognition is one of the most secure and authentic among the other biometrics and this field demands more authentic, reliable and fast algorithms to implement these biometric systems in real time. In this paper, an efficient localization technique is presented to identify pupil and iris boundaries using histogram of the iris image. Two small portions of iris have been used for polar transformation to reduce computational time and to increase the efficiency of the system. Wavelet transform is used for feature vector generation. Rotation of iris is compensated without shifts in the iris code. System is tested on Multimedia University Iris Database and results show that proposed system has encouraging performance.

  14. Automatic speech recognition

    Science.gov (United States)

    Espy-Wilson, Carol

    2005-04-01

    Great strides have been made in the development of automatic speech recognition (ASR) technology over the past thirty years. Most of this effort has been centered around the extension and improvement of Hidden Markov Model (HMM) approaches to ASR. Current commercially-available and industry systems based on HMMs can perform well for certain situational tasks that restrict variability such as phone dialing or limited voice commands. However, the holy grail of ASR systems is performance comparable to humans-in other words, the ability to automatically transcribe unrestricted conversational speech spoken by an infinite number of speakers under varying acoustic environments. This goal is far from being reached. Key to the success of ASR is effective modeling of variability in the speech signal. This tutorial will review the basics of ASR and the various ways in which our current knowledge of speech production, speech perception and prosody can be exploited to improve robustness at every level of the system.

  15. The Legal Recognition of Sign Languages

    Science.gov (United States)

    De Meulder, Maartje

    2015-01-01

    This article provides an analytical overview of the different types of explicit legal recognition of sign languages. Five categories are distinguished: constitutional recognition, recognition by means of general language legislation, recognition by means of a sign language law or act, recognition by means of a sign language law or act including…

  16. FILTWAM and Voice Emotion Recognition

    NARCIS (Netherlands)

    Bahreini, Kiavash; Nadolski, Rob; Westera, Wim

    2014-01-01

    This paper introduces the voice emotion recognition part of our framework for improving learning through webcams and microphones (FILTWAM). This framework enables multimodal emotion recognition of learners during game-based learning. The main goal of this study is to validate the use of microphone

  17. Face recognition using Krawtchouk moment

    Indian Academy of Sciences (India)

    Feature extraction is one of the important tasks in face recognition. Moments are widely used feature extractor due to their superior discriminatory power and geometrical invariance. Moments generally capture the global features of the image. This paper proposes Krawtchouk moment for feature extraction in face recognition ...

  18. Sign Facilitation in Word Recognition.

    Science.gov (United States)

    Wauters, Loes N.; Knoors, Harry E. T.; Vervloed, Mathijs P. J.; Aarnoutse, Cor A. J.

    2001-01-01

    This study examined whether use of sign language would facilitate reading word recognition by 16 deaf children (6- to 1 years-old) in the Netherlands. Results indicated that if words were learned through speech, accompanied by the relevant sign, accuracy of word recognition was greater than if words were learned solely through speech. (Contains…

  19. Iris Recognition - Beyond One Meter

    Science.gov (United States)

    Matey, James R.; Kennell, Lauren R.

    Iris recognition Iris recognition is, arguably, the most robust form of biometric Biometrics identification. It has been deployed in large-scale systems that have been very effective. The systems deployed to date make use of iris Remote Biometric cameras that require significant user cooperation; that in turn imposes significant constraints on the deployment scenarios that are practical.

  20. Methods of Teaching Speech Recognition

    Science.gov (United States)

    Rader, Martha H.; Bailey, Glenn A.

    2010-01-01

    Objective: This article introduces the history and development of speech recognition, addresses its role in the business curriculum, outlines related national and state standards, describes instructional strategies, and discusses the assessment of student achievement in speech recognition classes. Methods: Research methods included a synthesis of…

  1. Side-View Face Recognition

    NARCIS (Netherlands)

    Santemiz, P.; Spreeuwers, Lieuwe Jan; Veldhuis, Raymond N.J.

    2010-01-01

    Side-view face recognition is a challenging problem with many applications. Especially in real-life scenarios where the environment is uncontrolled, coping with pose variations up to side-view positions is an important task for face recognition. In this paper we discuss the use of side view face

  2. Forensic Face Recognition: A Survey

    NARCIS (Netherlands)

    Ali, Tauseef; Veldhuis, Raymond N.J.; Spreeuwers, Lieuwe Jan

    2010-01-01

    Beside a few papers which focus on the forensic aspects of automatic face recognition, there is not much published about it in contrast to the literature on developing new techniques and methodologies for biometric face recognition. In this report, we review forensic facial identification which is

  3. Side-View Face Recognition

    NARCIS (Netherlands)

    Santemiz, P.; Spreeuwers, Lieuwe Jan; Veldhuis, Raymond N.J.; van den Biggelaar, Olivier

    As a widely used biometrics, face recognition has many advantages such as being non-intrusive, natural and passive. On the other hand, in real-life scenarios with uncontrolled environment, pose variation up to side-view positions makes face recognition a challenging work. In this paper we discuss

  4. Recognition of emotion in others

    NARCIS (Netherlands)

    Frijda, N.H.; Paglieri, F.

    2012-01-01

    This chapter argues that recognition of emotion had a simple basis and a highly complex edifice above it. Its basis is formed by catching intent from expressive and other emotional behavior, using elementary principles of perceptual integration. In intent recognition, mirror neurons under particular

  5. Experience with digital mammography

    Directory of Open Access Journals (Sweden)

    G. P. Korzhenkova

    2011-01-01

    Full Text Available The use of digital techniques in mammography has become a last step for completing the process of digitization in diagnostic imaging. It is assumed that such a spatial decision will be required for digital mammography, as well as for high-resolution intensifying screen-film systems used in conventional mammography and that the digital techniques will be limited by the digitizer pixel size on detecting minor structures, such as microcalcifications. The introduction of digital technologies in mammography involves a tight control over an image and assures its high quality.

  6. Logic of the digital

    CERN Document Server

    Evens, Aden

    2015-01-01

    Building a foundational understanding of the digital, Logic of the Digital reveals a unique digital ontology. Beginning from formal and technical characteristics, especially the binary code at the core of all digital technologies, Aden Evens traces the pathways along which the digital domain of abstract logic encounters the material, human world. How does a code using only 0s and 1s give rise to the vast range of applications and information that constitutes a great and growing portion of our world? Evens' analysis shows how any encounter between the actual and the digital must cross an ontolo

  7. Playtesting The Digital Playground

    DEFF Research Database (Denmark)

    Majgaard, Gunver; Jessen, Carsten

    2009-01-01

    Being able to be absorbed in play in the digital playground is motivating for children who are used digital computer games. The children can play and exercise outdoors while using the same literacy as in indoor digital games. This paper presents a new playground product where an outdoor playground...... has been combined with digital games. The playground was tested in natural surroundings in a school yard and the findings about the interplay between digital and analog play are described here. Finally balancing in digital and analog games is discussed....

  8. Viewpoint Manifolds for Action Recognition

    Directory of Open Access Journals (Sweden)

    Souvenir Richard

    2009-01-01

    Full Text Available Abstract Action recognition from video is a problem that has many important applications to human motion analysis. In real-world settings, the viewpoint of the camera cannot always be fixed relative to the subject, so view-invariant action recognition methods are needed. Previous view-invariant methods use multiple cameras in both the training and testing phases of action recognition or require storing many examples of a single action from multiple viewpoints. In this paper, we present a framework for learning a compact representation of primitive actions (e.g., walk, punch, kick, sit that can be used for video obtained from a single camera for simultaneous action recognition and viewpoint estimation. Using our method, which models the low-dimensional structure of these actions relative to viewpoint, we show recognition rates on a publicly available dataset previously only achieved using multiple simultaneous views.

  9. Fast polygonal approximation of digital curves using relaxed straightness properties.

    Science.gov (United States)

    Bhowmick, Partha; Bhattacharya, Bhargab B

    2007-09-01

    Several existing DSS (digital straight line segment) recognition algorithms can be used to determine the digital straightness of a given one-pixel-thick digital curve. Because of the inherent geometric constraints of digital straightness, these algorithms often produce a large number of segments to cover a given digital curve representing a real-life object=image. Thus, a curve segment, which is not exactly digitally straight, but appears to be visually straight, is fragmented into multiple DSS when these algorithms are run. In this paper, a new concept of approximate straightness is introduced by relaxing certain conditions of DSS, and an algorithm is described to extract those segments from a digital curve. The number of such segments required to cover the curve is found to be significantly fewer than that of the exact DSS-cover. As a result, the data set required for representing a curve also reduces to a large extent. The extracted set of segments can further be combined to determine a compact polygonal approximation of a digital curve based on certain approximation criteria and a specified error tolerance. The proposed algorithm involves only primitive integer operations and thus runs very fast compared to those based on exact DSS. The overall time complexity becomes linear in the number of points present in the representative set. Experimental results on several digital curves demonstrate the speed, elegance and efficacy of the proposed method.

  10. AN APPLICATION OF SPEAKER RECOGNITION USING ARTIFICIAL NEURAL NETWORKS

    Directory of Open Access Journals (Sweden)

    Murat CANER

    2006-02-01

    Full Text Available In this study an artificial neural network (ANN is implemented, which has been used frequently as an implementation model in recent years, to recognize speaker identification. Generally, recognition is consist of three stages that, processing of signal, obtaining attributes and comparing them. Speech samples are transformed into digital data according to voice card of PC. In the analysis of voice stage, recurrent periods and white noise of voice data are trimmed by hamming window method and voice attribute part of the digital data is obtained. For obtaining attribute of voice data LPC (linear predictive coding and DFT (discrete fourier transform methods are used. Of those 28 coefficents, that is used for speaker recognition, 16 were obtained by the analysis of DFT and 12 were obtained by the analysis of LPC. The parameters that represent speaker voice, is used for training and test of ANN. Multilayer perceptron model is used as an architecture of ANN and backpropagation algorithm is used for training method. Voices of "a" is taken from 7 different person and their attributes are found. ANN is trained with these features to find the speaker who is the owner of the sample voice. And then using the test data that is not used for training part, recognition achievement of ANN is tested. As a result, good results were obtained with low failure rate.

  11. Speech Recognition: How Do We Teach It?

    Science.gov (United States)

    Barksdale, Karl

    2002-01-01

    States that growing use of speech recognition software has made voice writing an essential computer skill. Describes how to present the topic, develop basic speech recognition skills, and teach speech recognition outlining, writing, proofreading, and editing. (Contains 14 references.) (SK)

  12. Coastal California Digital Imagery

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This digital ortho-imagery dataset is a survey of coastal California. The project area consists of approximately 3774 square miles. The project design of the digital...

  13. Digital rectal exam

    Science.gov (United States)

    ... this page: //medlineplus.gov/ency/article/007069.htm Digital rectal exam To use the sharing features on this page, please enable JavaScript. A digital rectal exam is an examination of the lower ...

  14. Digital dannelse til gymnasieeleverne

    DEFF Research Database (Denmark)

    Kaarsted, Thomas; Holch Andersen, Knud

    2012-01-01

    Søsætningen af en ny tænketank skal udstikke nye digital retningslinjer for gymnasiekolerne. Baggrunden er en erkendelse af, at it-infrastruktur og digital teknologi ikke gør de alene.......Søsætningen af en ny tænketank skal udstikke nye digital retningslinjer for gymnasiekolerne. Baggrunden er en erkendelse af, at it-infrastruktur og digital teknologi ikke gør de alene....

  15. Basic digital signal processing

    CERN Document Server

    Lockhart, Gordon B

    1985-01-01

    Basic Digital Signal Processing describes the principles of digital signal processing and experiments with BASIC programs involving the fast Fourier theorem (FFT). The book reviews the fundamentals of the BASIC program, continuous and discrete time signals including analog signals, Fourier analysis, discrete Fourier transform, signal energy, power. The text also explains digital signal processing involving digital filters, linear time-variant systems, discrete time unit impulse, discrete-time convolution, and the alternative structure for second order infinite impulse response (IIR) sections.

  16. Digital asset management.

    Science.gov (United States)

    Humphrey, Clinton D; Tollefson, Travis T; Kriet, J David

    2010-05-01

    Facial plastic surgeons are accumulating massive digital image databases with the evolution of photodocumentation and widespread adoption of digital photography. Managing and maximizing the utility of these vast data repositories, or digital asset management (DAM), is a persistent challenge. Developing a DAM workflow that incorporates a file naming algorithm and metadata assignment will increase the utility of a surgeon's digital images. Copyright 2010 Elsevier Inc. All rights reserved.

  17. Developmental Changes in Face Recognition during Childhood: Evidence from Upright and Inverted Faces

    Science.gov (United States)

    de Heering, Adelaide; Rossion, Bruno; Maurer, Daphne

    2012-01-01

    Adults are experts at recognizing faces but there is controversy about how this ability develops with age. We assessed 6- to 12-year-olds and adults using a digitized version of the Benton Face Recognition Test, a sensitive tool for assessing face perception abilities. Children's response times for correct responses did not decrease between ages 6…

  18. Prediction of Word Recognition in the First Half of Grade 1

    Science.gov (United States)

    Snel, M. J.; Aarnoutse, C. A. J.; Terwel, J.; van Leeuwe, J. F. J.; van der Veld, W. M.

    2016-01-01

    Early detection of reading problems is important to prevent an enduring lag in reading skills. We studied the relationship between speed of word recognition (after six months of grade 1 education) and four kindergarten pre-literacy skills: letter knowledge, phonological awareness and naming speed for both digits and letters. Our sample consisted…

  19. Digitization in Maritime Industry

    DEFF Research Database (Denmark)

    Constantiou, Ioanna; Shollo, Arisa; Kreiner, Kristian

    2017-01-01

    Digitization in the maritime industry is expected to transform businesses. The recently introduced mobile technologies in inter-organizational processes is an example of digitization in an industry which moves very slowly towards digital transformation. We focus on the influence of mobile...

  20. Reconceptualising Critical Digital Literacy

    Science.gov (United States)

    Pangrazio, Luciana

    2016-01-01

    While it has proved a useful concept during the past 20 years, the notion of "critical digital literacy" requires rethinking in light of the fast-changing nature of young people's digital practices. This paper contrasts long-established notions of "critical digital literacy" (based primarily around the critical consumption of…

  1. Mass Digitization of Books

    Science.gov (United States)

    Coyle, Karen

    2006-01-01

    Mass digitization of the bound volumes that we generally call "books" has begun, and, thanks to the interest in Google and all that it does, it is getting widespread media attention. The Open Content Alliance (OCA), a library initiative formed after Google announced its library book digitization project, has brought library digitization projects…

  2. Preparing collections for digitization

    CERN Document Server

    Bulow, Anna E

    2010-01-01

    Most libraries, archives and museums are confronting the challenges of providing digital access to their collections. This guide offers guidance covering the end-to-end process of digitizing collections, from selecting records for digitization to choosing suppliers and equipment and dealing with documents that present individual problems.

  3. Behandlingseffekt af Digital Dermatitis

    DEFF Research Database (Denmark)

    Krogh, Kenneth; Thomsen, Peter

    2008-01-01

    af klovlidelser herunder især Digital Dermatitis. Klovregistreringerne viser, at der er stor dynamik og mange nyinfektioner af Digital Dermatitis svarende til problematikken ved mastitis. Behandlingseffekten ved Digital Dermatitis er høj (omkring 90 %) ved den udførte behandling. Behandlingen bestod...

  4. Personal Digital Video Stories

    DEFF Research Database (Denmark)

    Ørngreen, Rikke; Henningsen, Birgitte Sølbeck; Louw, Arnt Vestergaard

    2016-01-01

    agenda focusing on video productions in combination with digital storytelling, followed by a presentation of the digital storytelling features. The paper concludes with a suggestion to initiate research in what is identified as Personal Digital Video (PDV) Stories within longitudinal settings, while...

  5. Pattern recognition in spectra

    Science.gov (United States)

    Gebran, M.; Paletou, F.

    2017-06-01

    We present a new automated procedure that simultaneously derives the effective temperature Teff, surface gravity log g, metallicity [Fe/H], and equatorial projected rotational velocity ve sin i for stars. The procedure is inspired by the well-known PCA-based inversion of spectropolarimetric full-Stokes solar data, which was used both for Zeeman and Hanle effects. The efficiency and accuracy of this procedure have been proven for FGK, A, and late type dwarf stars of K and M spectral types. Learning databases are generated from the Elodie stellar spectra library using observed spectra for which fundamental parameters were already evaluated or with synthetic data. The synthetic spectra are calculated using ATLAS9 model atmospheres. This technique helped us to detect many peculiar stars such as Am, Ap, HgMn, SiEuCr and binaries. This fast and efficient technique could be used every time a pattern recognition is needed. One important application is the understanding of the physical properties of planetary surfaces by comparing aboard instrument data to synthetic ones.

  6. Arabic character recognition

    Science.gov (United States)

    Allam, May

    1994-03-01

    This paper presents a complete system for learning and recognizing Arabic characters. Arabic OCR faces technical problems not encountered in other languages such as cursiveness, overriding and overlapping of characters, multiple shapes per character and the presence of vowels above and below the characters. The proposed approach relies on the fact that the process of connecting Arabic characters to produce cursive writing tends to form a fictitious baseline. During preprocessing, contour analysis provides both component isolation and baseline location. In the feature extraction phase, the words are processed from right to left to generate a sequence of labels. Each label is one of a predetermined codebook that represents all possible bit distribution with respect to the baseline. At a certain position, which depends on the label context, a segmentation decision is taken. During training, a model is generated for each character. This model describes the probability of the occurrence of the labels at each vertical position. During recognition, the probability of the label observation sequence is computed and accumulated. The system has been tested on different typewritten, typeset fonts and diacriticized versions of both and the evaluation results are presented.

  7. Kernel learning algorithms for face recognition

    CERN Document Server

    Li, Jun-Bao; Pan, Jeng-Shyang

    2013-01-01

    Kernel Learning Algorithms for Face Recognition covers the framework of kernel based face recognition. This book discusses the advanced kernel learning algorithms and its application on face recognition. This book also focuses on the theoretical deviation, the system framework and experiments involving kernel based face recognition. Included within are algorithms of kernel based face recognition, and also the feasibility of the kernel based face recognition method. This book provides researchers in pattern recognition and machine learning area with advanced face recognition methods and its new

  8. Vision-Based Navigation and Recognition

    National Research Council Canada - National Science Library

    Rosenfeld, Azriel

    1996-01-01

    .... (4) Invariants -- both geometric and other types. (5) Human faces: Analysis of images of human faces, including feature extraction, face recognition, compression, and recognition of facial expressions...

  9. Vision-Based Navigation and Recognition

    National Research Council Canada - National Science Library

    Rosenfeld, Azriel

    1998-01-01

    .... (4) Invariants: both geometric and other types. (5) Human faces: Analysis of images of human faces, including feature extraction, face recognition, compression, and recognition of facial expressions...

  10. CHARACTER RECOGNITION OF VIDEO SUBTITLES\\

    Directory of Open Access Journals (Sweden)

    Satish S Hiremath

    2016-11-01

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

  11. Face Recognition using Approximate Arithmetic

    DEFF Research Database (Denmark)

    Marso, Karol

    Face recognition is image processing technique which aims to identify human faces and found its use in various different fields for example in security. Throughout the years this field evolved and there are many approaches and many different algorithms which aim to make the face recognition as effective...... processing applications the results do not need to be completely precise and use of the approximate arithmetic can lead to reduction in terms of delay, space and power consumption. In this paper we examine possible use of approximate arithmetic in face recognition using Eigenfaces algorithm....

  12. Facial recognition in education system

    Science.gov (United States)

    Krithika, L. B.; Venkatesh, K.; Rathore, S.; Kumar, M. Harish

    2017-11-01

    Human beings exploit emotions comprehensively for conveying messages and their resolution. Emotion detection and face recognition can provide an interface between the individuals and technologies. The most successful applications of recognition analysis are recognition of faces. Many different techniques have been used to recognize the facial expressions and emotion detection handle varying poses. In this paper, we approach an efficient method to recognize the facial expressions to track face points and distances. This can automatically identify observer face movements and face expression in image. This can capture different aspects of emotion and facial expressions.

  13. Iris recognition via plenoptic imaging

    Energy Technology Data Exchange (ETDEWEB)

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

    2017-11-07

    Iris recognition can be accomplished for a wide variety of eye images by using plenoptic imaging. Using plenoptic technology, it is possible to correct focus after image acquisition. One example technology reconstructs images having different focus depths and stitches them together, resulting in a fully focused image, even in an off-angle gaze scenario. Another example technology determines three-dimensional data for an eye and incorporates it into an eye model used for iris recognition processing. Another example technology detects contact lenses. Application of the technologies can result in improved iris recognition under a wide variety of scenarios.

  14. Genetic Algorithm based Gait Recognition

    OpenAIRE

    R.Ashok Kumar Reddy; G. Venkata Narasimhulu; Dr. S. A. K. Jilani; Dr D.Seshappa

    2013-01-01

    In this paper, a face/gait recognition system for personal identification and verification using genetic algorithm. This face/gait Recognition System (FRS/GRS) is also being trained for gender identification. The Face/Gait recognition system consists of three steps. At the very outset some pre-processing are applied on the input image. Secondly face/gait features are extracted, which will be taken as the input of the BPNN and genetic algorithm (GA) in the third step and classification is carr...

  15. Use of Adaptive Digital Signal Processing to Improve Speech Communication for Normally Hearing aand Hearing-Impaired Subjects.

    Science.gov (United States)

    Harris, Richard W.; And Others

    1988-01-01

    A two-microphone adaptive digital noise cancellation technique improved word-recognition ability for 20 normal and 12 hearing-impaired adults by reducing multitalker speech babble and speech spectrum noise 18-22 dB. Word recognition improvements averaged 37-50 percent for normal and 27-40 percent for hearing-impaired subjects. Improvement was best…

  16. Recurrent Convolutional Neural Networks: A Better Model of Biological Object Recognition.

    Science.gov (United States)

    Spoerer, Courtney J; McClure, Patrick; Kriegeskorte, Nikolaus

    2017-01-01

    Feedforward neural networks provide the dominant model of how the brain performs visual object recognition. However, these networks lack the lateral and feedback connections, and the resulting recurrent neuronal dynamics, of the ventral visual pathway in the human and non-human primate brain. Here we investigate recurrent convolutional neural networks with bottom-up (B), lateral (L), and top-down (T) connections. Combining these types of connections yields four architectures (B, BT, BL, and BLT), which we systematically test and compare. We hypothesized that recurrent dynamics might improve recognition performance in the challenging scenario of partial occlusion. We introduce two novel occluded object recognition tasks to test the efficacy of the models, digit clutter (where multiple target digits occlude one another) and digit debris (where target digits are occluded by digit fragments). We find that recurrent neural networks outperform feedforward control models (approximately matched in parametric complexity) at recognizing objects, both in the absence of occlusion and in all occlusion conditions. Recurrent networks were also found to be more robust to the inclusion of additive Gaussian noise. Recurrent neural networks are better in two respects: (1) they are more neurobiologically realistic than their feedforward counterparts; (2) they are better in terms of their ability to recognize objects, especially under challenging conditions. This work shows that computer vision can benefit from using recurrent convolutional architectures and suggests that the ubiquitous recurrent connections in biological brains are essential for task performance.

  17. Digital disruption ?syndromes.

    Science.gov (United States)

    Sullivan, Clair; Staib, Andrew

    2017-05-18

    The digital transformation of hospitals in Australia is occurring rapidly in order to facilitate innovation and improve efficiency. Rapid transformation can cause temporary disruption of hospital workflows and staff as processes are adapted to the new digital workflows. The aim of this paper is to outline various types of digital disruption and some strategies for effective management. A large tertiary university hospital recently underwent a rapid, successful roll-out of an integrated electronic medical record (EMR). We observed this transformation and propose several digital disruption "syndromes" to assist with understanding and management during digital transformation: digital deceleration, digital transparency, digital hypervigilance, data discordance, digital churn and post-digital 'depression'. These 'syndromes' are defined and discussed in detail. Successful management of this temporary digital disruption is important to ensure a successful transition to a digital platform.What is known about this topic? Digital disruption is defined as the changes facilitated by digital technologies that occur at a pace and magnitude that disrupt established ways of value creation, social interactions, doing business and more generally our thinking. Increasing numbers of Australian hospitals are implementing digital solutions to replace traditional paper-based systems for patient care in order to create opportunities for improved care and efficiencies. Such large scale change has the potential to create transient disruption to workflows and staff. Managing this temporary disruption effectively is an important factor in the successful implementation of an EMR.What does this paper add? A large tertiary university hospital recently underwent a successful rapid roll-out of an integrated electronic medical record (EMR) to become Australia's largest digital hospital over a 3-week period. We observed and assisted with the management of several cultural, behavioural and

  18. Ageing and digital games

    DEFF Research Database (Denmark)

    Iversen, Sara Mosberg

    Digital games are still to a great degree considered a medium mainly for young boys. However, available statistics on Western media use show that this is far from the case. Increasingly, people of all ages and genders play digital games, also older adults in their early 60s and beyond. The aim...... of the book is to examine, analyse and discuss: 1) What older adults do with digital games and what meanings the use of digital games take on in the everyday life of older adults; 2) How older adults are perceived by society in relation to digital games; 3) How play and games can be used both...

  19. Digital Living at Home

    DEFF Research Database (Denmark)

    Andersen, Pernille Viktoria Kathja; Christiansen, Ellen Tove

    2013-01-01

    Does living with digital technology inevitably lead to digital living? Users talking about a digital home control system, they have had in their homes for eight years, indicate that there is more to living with digital technology than a functional-operational grip on regulation. Our analysis...... of these user voices has directed us towards a ‘home-keeping’ design discourse, which opens new horizons for design of digital home control systems by allowing users to perform as self-determined controllers and groomers of their habitat. The paper concludes by outlining the implications of a ‘home...

  20. Unequal recognition, misrecognition and injustice

    DEFF Research Database (Denmark)

    Lægaard, Sune

    2012-01-01

    Euro-multiculturalism is (1) concerned with religiously defined immigrant minorities; (2) sees policies of recognition as a means to secure multicultural equality between groups; (3) endorses the moderate secularism of European states; and (4) adopts a contextualist approach to answering the norm......Euro-multiculturalism is (1) concerned with religiously defined immigrant minorities; (2) sees policies of recognition as a means to secure multicultural equality between groups; (3) endorses the moderate secularism of European states; and (4) adopts a contextualist approach to answering...... by the state of religious minorities. It argues that state–religion relations can be analysed as relations of recognition, which are not only unequal but also multi-dimensional, and that it is difficult to answer the question whether multi-dimensional recognitive inequalities are unjust or wrong if one...

  1. On speech recognition during anaesthesia

    DEFF Research Database (Denmark)

    Alapetite, Alexandre

    2007-01-01

    This PhD thesis in human-computer interfaces (informatics) studies the case of the anaesthesia record used during medical operations and the possibility to supplement it with speech recognition facilities. Problems and limitations have been identified with the traditional paper-based anaesthesia...... interface with speech input facilities in Danish. The evaluation of the new interface was carried out in a full-scale anaesthesia simulator. This has been complemented by laboratory experiments on several aspects of speech recognition for this type of use, e.g. the effects of noise on speech recognition...... accuracy. Finally, the last part of the thesis looks at the acceptance and success of a speech recognition system introduced in a Danish hospital to produce patient records....

  2. Similarity measures for face recognition

    CERN Document Server

    Vezzetti, Enrico

    2015-01-01

    Face recognition has several applications, including security, such as (authentication and identification of device users and criminal suspects), and in medicine (corrective surgery and diagnosis). Facial recognition programs rely on algorithms that can compare and compute the similarity between two sets of images. This eBook explains some of the similarity measures used in facial recognition systems in a single volume. Readers will learn about various measures including Minkowski distances, Mahalanobis distances, Hansdorff distances, cosine-based distances, among other methods. The book also summarizes errors that may occur in face recognition methods. Computer scientists "facing face" and looking to select and test different methods of computing similarities will benefit from this book. The book is also useful tool for students undertaking computer vision courses.

  3. Genetic specificity of face recognition

    National Research Council Canada - National Science Library

    Nicholas G. Shakeshaft; Robert Plomin

    2015-01-01

    ...), both phenotypically and genetically. Recent twin studies have found the ability to memorize and recognize faces to be an exception, being similarly heritable but phenotypically substantially uncorrelated both with g and with general object recognition...

  4. Pattern recognition and string matching

    CERN Document Server

    Cheng, Xiuzhen

    2002-01-01

    The research and development of pattern recognition have proven to be of importance in science, technology, and human activity. Many useful concepts and tools from different disciplines have been employed in pattern recognition. Among them is string matching, which receives much theoretical and practical attention. String matching is also an important topic in combinatorial optimization. This book is devoted to recent advances in pattern recognition and string matching. It consists of twenty eight chapters written by different authors, addressing a broad range of topics such as those from classifica­ tion, matching, mining, feature selection, and applications. Each chapter is self-contained, and presents either novel methodological approaches or applications of existing theories and techniques. The aim, intent, and motivation for publishing this book is to pro­ vide a reference tool for the increasing number of readers who depend upon pattern recognition or string matching in some way. This includes student...

  5. Investigation on Optimization in Segmentation Phase of Iris Recognition

    Directory of Open Access Journals (Sweden)

    Selvamuthukumaran Shanmugam

    2010-01-01

    Full Text Available In a progressively more digital society, the demandfor secure identification has led to amplified development ofbiometric systems. Iris biometric systems are becoming widelyadopted and accepted as one of the most effective ways topositively identify people. In this paper, the Segmentation phasesof Iris recognition has been examined. The performance of theSegmentation phase could be amplified by the proposedoptimization technique- Optimized Iris Segmentation using SobelEdge Detection. By the proposed method, the overall rank-onerecognition rate of 90% is being achieved which is much betterthan reported accuracies for iris recognition in the literature.Also the proposed approach makes the overall iris recognitionsystem performance by the improvement factor of 10 fold as well.

  6. Two dimensional convolute integers for machine vision and image recognition

    Science.gov (United States)

    Edwards, Thomas R.

    1988-01-01

    Machine vision and image recognition require sophisticated image processing prior to the application of Artificial Intelligence. Two Dimensional Convolute Integer Technology is an innovative mathematical approach for addressing machine vision and image recognition. This new technology generates a family of digital operators for addressing optical images and related two dimensional data sets. The operators are regression generated, integer valued, zero phase shifting, convoluting, frequency sensitive, two dimensional low pass, high pass and band pass filters that are mathematically equivalent to surface fitted partial derivatives. These operators are applied non-recursively either as classical convolutions (replacement point values), interstitial point generators (bandwidth broadening or resolution enhancement), or as missing value calculators (compensation for dead array element values). These operators show frequency sensitive feature selection scale invariant properties. Such tasks as boundary/edge enhancement and noise or small size pixel disturbance removal can readily be accomplished. For feature selection tight band pass operators are essential. Results from test cases are given.

  7. COMPRESSIVE CLASSIFICATION FOR FACE RECOGNITION

    OpenAIRE

    Majumdar, Angshul; Ward, Rabab K.

    2010-01-01

    This chapter reviews an alternate face recognition method than those provided by traditional machine learning tools. Conventional machine learning solutions to dimensionality reduction and classification require all the data to be present beforehand, i.e. whenever new data is added, the system cannot be updated in online fashion, rather all the calculations need to be re-done from scratch. This creates a computational bottleneck for large scale implementation of face recognition systems.

  8. Recognition Memory in Psychotic Patients

    Directory of Open Access Journals (Sweden)

    H. Ellis

    1992-01-01

    Full Text Available Preliminary data are reported from experiments in which Warrington's (1984 Recognition Memory Tests were given to patients with misidentification delusions including the Capgras type and to psychotic patients. The results showed a profound impairment on face recognition for most groups, especially those with the Capgras delusion. It was rare to find a patent whose score on the word test was anything but normal.

  9. Bidirectional Modulation of Recognition Memory

    OpenAIRE

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

    2015-01-01

    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, per...

  10. An automatic image recognition approach

    Directory of Open Access Journals (Sweden)

    Tudor Barbu

    2007-07-01

    Full Text Available Our paper focuses on the graphical analysis domain. We propose an automatic image recognition technique. This approach consists of two main pattern recognition steps. First, it performs an image feature extraction operation on an input image set, using statistical dispersion features. Then, an unsupervised classification process is performed on the previously obtained graphical feature vectors. An automatic region-growing based clustering procedure is proposed and utilized in the classification stage.

  11. [Neurological disease and facial recognition].

    Science.gov (United States)

    Kawamura, Mitsuru; Sugimoto, Azusa; Kobayakawa, Mutsutaka; Tsuruya, Natsuko

    2012-07-01

    To discuss the neurological basis of facial recognition, we present our case reports of impaired recognition and a review of previous literature. First, we present a case of infarction and discuss prosopagnosia, which has had a large impact on face recognition research. From a study of patient symptoms, we assume that prosopagnosia may be caused by unilateral right occipitotemporal lesion and right cerebral dominance of facial recognition. Further, circumscribed lesion and degenerative disease may also cause progressive prosopagnosia. Apperceptive prosopagnosia is observed in patients with posterior cortical atrophy (PCA), pathologically considered as Alzheimer's disease, and associative prosopagnosia in frontotemporal lobar degeneration (FTLD). Second, we discuss face recognition as part of communication. Patients with Parkinson disease show social cognitive impairments, such as difficulty in facial expression recognition and deficits in theory of mind as detected by the reading the mind in the eyes test. Pathological and functional imaging studies indicate that social cognitive impairment in Parkinson disease is possibly related to damages in the amygdalae and surrounding limbic system. The social cognitive deficits can be observed in the early stages of Parkinson disease, and even in the prodromal stage, for example, patients with rapid eye movement (REM) sleep behavior disorder (RBD) show impairment in facial expression recognition. Further, patients with myotonic dystrophy type 1 (DM 1), which is a multisystem disease that mainly affects the muscles, show social cognitive impairment similar to that of Parkinson disease. Our previous study showed that facial expression recognition impairment of DM 1 patients is associated with lesion in the amygdalae and insulae. Our study results indicate that behaviors and personality traits in DM 1 patients, which are revealed by social cognitive impairment, are attributable to dysfunction of the limbic system.

  12. Human Activity Recognition using Smartphone

    OpenAIRE

    Rasekh, Amin; Chen, Chien-An; Lu, Yan

    2014-01-01

    Human activity recognition has wide applications in medical research and human survey system. In this project, we design a robust activity recognition system based on a smartphone. The system uses a 3-dimentional smartphone accelerometer as the only sensor to collect time series signals, from which 31 features are generated in both time and frequency domain. Activities are classified using 4 different passive learning methods, i.e., quadratic classifier, k-nearest neighbor algorithm, support ...

  13. Pattern-Recognition Processor Using Holographic Photopolymer

    Science.gov (United States)

    Chao, Tien-Hsin; Cammack, Kevin

    2006-01-01

    proposed joint-transform optical correlator (JTOC) would be capable of operating as a real-time pattern-recognition processor. The key correlation-filter reading/writing medium of this JTOC would be an updateable holographic photopolymer. The high-resolution, high-speed characteristics of this photopolymer would enable pattern-recognition processing to occur at a speed three orders of magnitude greater than that of state-of-the-art digital pattern-recognition processors. There are many potential applications in biometric personal identification (e.g., using images of fingerprints and faces) and nondestructive industrial inspection. In order to appreciate the advantages of the proposed JTOC, it is necessary to understand the principle of operation of a conventional JTOC. In a conventional JTOC (shown in the upper part of the figure), a collimated laser beam passes through two side-by-side spatial light modulators (SLMs). One SLM displays a real-time input image to be recognized. The other SLM displays a reference image from a digital memory. A Fourier-transform lens is placed at its focal distance from the SLM plane, and a charge-coupled device (CCD) image detector is placed at the back focal plane of the lens for use as a square-law recorder. Processing takes place in two stages. In the first stage, the CCD records the interference pattern between the Fourier transforms of the input and reference images, and the pattern is then digitized and saved in a buffer memory. In the second stage, the reference SLM is turned off and the interference pattern is fed back to the input SLM. The interference pattern thus becomes Fourier-transformed, yielding at the CCD an image representing the joint-transform correlation between the input and reference images. This image contains a sharp correlation peak when the input and reference images are matched. The drawbacks of a conventional JTOC are the following: The CCD has low spatial resolution and is not an ideal square

  14. Optical and digital techniques for information security

    CERN Document Server

    2005-01-01

    Optical and Digital Techniques for Information Security is the first book in a series focusing on Advanced Sciences and Technologies for Security Applications. This book encompases the results of research investigation and technologies used to secure, verify, recognize, track, and authenticate objects and information from theft, counterfeiting, and manipulation by unauthorized persons and agencies. This Information Security book will draw on the diverse expertise in optical sciences and engineering, digital image processing, imaging systems, information processing, computer based information systems, sensors, detectors, and biometrics to report innovative technologies that can be applied to information security issues. The Advanced Sciences and Technologies for Security Applications series focuses on research monographs in the areas of: -Recognition and identification (including optical imaging, biometrics, authentication, verification, and smart surveillance systems) -Biological and chemical threat detection...

  15. Voice congruency facilitates word recognition.

    Directory of Open Access Journals (Sweden)

    Sandra Campeanu

    Full Text Available Behavioral studies of spoken word memory have shown that context congruency facilitates both word and source recognition, though the level at which context exerts its influence remains equivocal. We measured event-related potentials (ERPs while participants performed both types of recognition task with words spoken in four voices. Two voice parameters (i.e., gender and accent varied between speakers, with the possibility that none, one or two of these parameters was congruent between study and test. Results indicated that reinstating the study voice at test facilitated both word and source recognition, compared to similar or no context congruency at test. Behavioral effects were paralleled by two ERP modulations. First, in the word recognition test, the left parietal old/new effect showed a positive deflection reflective of context congruency between study and test words. Namely, the same speaker condition provided the most positive deflection of all correctly identified old words. In the source recognition test, a right frontal positivity was found for the same speaker condition compared to the different speaker conditions, regardless of response success. Taken together, the results of this study suggest that the benefit of context congruency is reflected behaviorally and in ERP modulations traditionally associated with recognition memory.

  16. Pattern recognition receptors: an update.

    Science.gov (United States)

    Goutagny, Nadege; Fitzgerald, Katherine A

    2006-07-01

    The vertebrate immune system consists of two inter-related components, the innate and adaptive responses, which are required for the resolution of infection. The innate immune response is critical for the immediate protection from infection and for marshalling the B- and T-cell responses of the adaptive response. A key component of the innate immune response is germline-encoded pattern recognition receptors that detect pathogens. Several families of these pattern recognition receptors have now been described. Microbial recognition by these receptors triggers appropriate immune responses, including the direct uptake and killing of pathogens and/or initiation of intracellular signaling pathways that culminate in the activation of immune responsive transcriptional programs. Pattern recognition receptors include soluble receptors in serum (collectins), transmembrane receptors on cell surfaces or vacuolar membranes (C-type lectins and Toll-like receptors) or cytoplasmic sensors (NACHT-LRR proteins and RNA helicases). Roles for these pattern recognition receptor families are emerging in the susceptibility to bacterial and viral infections and in acute and chronic conditions, such as sepsis, autoimmune disease and atherosclerosis. These findings suggest that the selective targeting of pattern recognition receptors and the pathways they trigger may be useful clinically. Progress towards therapeutics designed to target Toll-like receptor signaling is already well underway. This review will describe our current understanding of innate immune sensors and the mechanisms regulating their activity.

  17. Fuzzy-based multi-kernel spherical support vector machine for ...

    Indian Academy of Sciences (India)

    A K Sampath

    2017-08-08

    Aug 8, 2017 ... Abstract. Due to constant advancement of computer tools, automated conversion of images of typed, handwritten and printed text is important for various applications, which has led to intense research for several years in the field of offline handwritten character recognition. Handwritten character recognition ...

  18. Handwriting segmentation of unconstrained Oriya text

    Indian Academy of Sciences (India)

    Indian language; Oriya script; character segmentation; handwriting recognition. 1. Introduction. Segmentation of handwritten text into lines, words and characters is one of the important steps in the handwritten script recognition process. The task of individual text-line segmentation from unconstrained handwritten documents ...

  19. Filter and Filter Bank Design for Image Texture Recognition

    Energy Technology Data Exchange (ETDEWEB)

    Randen, Trygve

    1997-12-31

    The relevance of this thesis to energy and environment lies in its application to remote sensing such as for instance sea floor mapping and seismic pattern recognition. The focus is on the design of two-dimensional filters for feature extraction, segmentation, and classification of digital images with textural content. The features are extracted by filtering with a linear filter and estimating the local energy in the filter response. The thesis gives a review covering broadly most previous approaches to texture feature extraction and continues with proposals of some new techniques. 143 refs., 59 figs., 7 tabs.

  20. Comparing Face Detection and Recognition Techniques

    OpenAIRE

    Korra, Jyothi

    2016-01-01

    This paper implements and compares different techniques for face detection and recognition. One is find where the face is located in the images that is face detection and second is face recognition that is identifying the person. We study three techniques in this paper: Face detection using self organizing map (SOM), Face recognition by projection and nearest neighbor and Face recognition using SVM.

  1. Identification of Alfalfa Leaf Diseases Using Image Recognition Technology

    Science.gov (United States)

    Qin, Feng; Liu, Dongxia; Sun, Bingda; Ruan, Liu; Ma, Zhanhong; Wang, Haiguang

    2016-01-01

    Common leaf spot (caused by Pseudopeziza medicaginis), rust (caused by Uromyces striatus), Leptosphaerulina leaf spot (caused by Leptosphaerulina briosiana) and Cercospora leaf spot (caused by Cercospora medicaginis) are the four common types of alfalfa leaf diseases. Timely and accurate diagnoses of these diseases are critical for disease management, alfalfa quality control and the healthy development of the alfalfa industry. In this study, the identification and diagnosis of the four types of alfalfa leaf diseases were investigated using pattern recognition algorithms based on image-processing technology. A sub-image with one or multiple typical lesions was obtained by artificial cutting from each acquired digital disease image. Then the sub-images were segmented using twelve lesion segmentation methods integrated with clustering algorithms (including K_means clustering, fuzzy C-means clustering and K_median clustering) and supervised classification algorithms (including logistic regression analysis, Naive Bayes algorithm, classification and regression tree, and linear discriminant analysis). After a comprehensive comparison, the segmentation method integrating the K_median clustering algorithm and linear discriminant analysis was chosen to obtain lesion images. After the lesion segmentation using this method, a total of 129 texture, color and shape features were extracted from the lesion images. Based on the features selected using three methods (ReliefF, 1R and correlation-based feature selection), disease recognition models were built using three supervised learning methods, including the random forest, support vector machine (SVM) and K-nearest neighbor methods. A comparison of the recognition results of the models was conducted. The results showed that when the ReliefF method was used for feature selection, the SVM model built with the most important 45 features (selected from a total of 129 features) was the optimal model. For this SVM model, the

  2. Identification of Alfalfa Leaf Diseases Using Image Recognition Technology.

    Directory of Open Access Journals (Sweden)

    Feng Qin

    Full Text Available Common leaf spot (caused by Pseudopeziza medicaginis, rust (caused by Uromyces striatus, Leptosphaerulina leaf spot (caused by Leptosphaerulina briosiana and Cercospora leaf spot (caused by Cercospora medicaginis are the four common types of alfalfa leaf diseases. Timely and accurate diagnoses of these diseases are critical for disease management, alfalfa quality control and the healthy development of the alfalfa industry. In this study, the identification and diagnosis of the four types of alfalfa leaf diseases were investigated using pattern recognition algorithms based on image-processing technology. A sub-image with one or multiple typical lesions was obtained by artificial cutting from each acquired digital disease image. Then the sub-images were segmented using twelve lesion segmentation methods integrated with clustering algorithms (including K_means clustering, fuzzy C-means clustering and K_median clustering and supervised classification algorithms (including logistic regression analysis, Naive Bayes algorithm, classification and regression tree, and linear discriminant analysis. After a comprehensive comparison, the segmentation method integrating the K_median clustering algorithm and linear discriminant analysis was chosen to obtain lesion images. After the lesion segmentation using this method, a total of 129 texture, color and shape features were extracted from the lesion images. Based on the features selected using three methods (ReliefF, 1R and correlation-based feature selection, disease recognition models were built using three supervised learning methods, including the random forest, support vector machine (SVM and K-nearest neighbor methods. A comparison of the recognition results of the models was conducted. The results showed that when the ReliefF method was used for feature selection, the SVM model built with the most important 45 features (selected from a total of 129 features was the optimal model. For this SVM model, the

  3. Identification of Alfalfa Leaf Diseases Using Image Recognition Technology.

    Science.gov (United States)

    Qin, Feng; Liu, Dongxia; Sun, Bingda; Ruan, Liu; Ma, Zhanhong; Wang, Haiguang

    2016-01-01

    Common leaf spot (caused by Pseudopeziza medicaginis), rust (caused by Uromyces striatus), Leptosphaerulina leaf spot (caused by Leptosphaerulina briosiana) and Cercospora leaf spot (caused by Cercospora medicaginis) are the four common types of alfalfa leaf diseases. Timely and accurate diagnoses of these diseases are critical for disease management, alfalfa quality control and the healthy development of the alfalfa industry. In this study, the identification and diagnosis of the four types of alfalfa leaf diseases were investigated using pattern recognition algorithms based on image-processing technology. A sub-image with one or multiple typical lesions was obtained by artificial cutting from each acquired digital disease image. Then the sub-images were segmented using twelve lesion segmentation methods integrated with clustering algorithms (including K_means clustering, fuzzy C-means clustering and K_median clustering) and supervised classification algorithms (including logistic regression analysis, Naive Bayes algorithm, classification and regression tree, and linear discriminant analysis). After a comprehensive comparison, the segmentation method integrating the K_median clustering algorithm and linear discriminant analysis was chosen to obtain lesion images. After the lesion segmentation using this method, a total of 129 texture, color and shape features were extracted from the lesion images. Based on the features selected using three methods (ReliefF, 1R and correlation-based feature selection), disease recognition models were built using three supervised learning methods, including the random forest, support vector machine (SVM) and K-nearest neighbor methods. A comparison of the recognition results of the models was conducted. The results showed that when the ReliefF method was used for feature selection, the SVM model built with the most important 45 features (selected from a total of 129 features) was the optimal model. For this SVM model, the

  4. Micro-Recognition - Erving Goffman as Recognition Thinker

    DEFF Research Database (Denmark)

    Jacobsen, Michael Hviid; Kristiansen, Søren

    2009-01-01

    and civil inattention guide the conduct of people in many of their face-to-face encounters with each other. This article therefore shows how Goffman may in fact supplement many of the most fashionable and celebrated contemporary recognition theories as advanced by e.g. Nancy Fraser, Charles Taylor or Axel......  The purpose of this article is to present, develop and exemplify the argument that Erving Goffman can be regarded as an important yet somewhat overlooked contributor to recognition theory in contemporary sociology. Despite often being neglected in this respect, this article provides...... an interpretation of Goffman as a major recognition theorist on the micro-level of social analysis by way of his ritual metaphor. Erving Goffman's sociology is conventionally approached and appreciated primarily through his famous dramaturgical metaphor that describes and comprehends social life through...

  5. Digital radiography: an overview.

    Science.gov (United States)

    Parks, Edwin T; Williamson, Gail F

    2002-11-15

    Since the discovery of X-rays in 1895, film has been the primary medium for capturing, displaying, and storing radiographic images. It is a technology that dental practitioners are the most familiar and comfortable with in terms of technique and interpretation. Digital radiography is the latest advancement in dental imaging and is slowly being adopted by the dental profession. Digital imaging incorporates computer technology in the capture, display, enhancement, and storage of direct radiographic images. Digital imaging offers some distinct advantages over film, but like any emerging technology, it presents new and different challenges for the practitioner to overcome. This article presents an overview of digital imaging including basic terminology and comparisons with film-based imaging. The principles of direct and indirect digital imaging modalities, intraoral and extraoral applications, image processing, and diagnostic efficacy will be discussed. In addition, the article will provide a list of questions dentists should consider prior to purchasing digital imaging systems for their practice.

  6. Digital gaming expertise

    DEFF Research Database (Denmark)

    Toft-Nielsen, Claus

    In a digitally saturated environment digital media users of all kinds, engaged in different areas of activity, are increasingly categorized in terms of their ability to appropriate and use digital media – they are regarded as non-users, experts, natives, or literates for instance. Within...... communication and game studies there are multiple understandings of how digital expertise is expressed and performed, and subsequently how these expressions and performances can be valued, understood and theorized within the research community. Among other things expertise with and within digital games has...... – rather, this is an paper that develops an understanding of how digital media expertise emerge and is negotiated among everyday gamers in domestic contexts. The paper is based on empirical data from qualitative focus group interviews (Morgan, 1997) and participant observations in-game and out...

  7. Theory of Digital Automata

    CERN Document Server

    Borowik, Bohdan; Lahno, Valery; Petrov, Oleksandr

    2013-01-01

    This book serves a dual purpose: firstly to combine the treatment of circuits and digital electronics, and secondly, to establish a strong connection with the contemporary world of digital systems. The need for this approach arises from the observation that introducing digital electronics through a course in traditional circuit analysis is fast becoming obsolete. Our world has gone digital. Automata theory helps with the design of digital circuits such as parts of computers, telephone systems and control systems. A complete perspective is emphasized, because even the most elegant computer architecture will not function without adequate supporting circuits. The focus is on explaining the real-world implementation of complete digital systems. In doing so, the reader is prepared to immediately begin design and implementation work. This work serves as a bridge to take readers from the theoretical world to the everyday design world where solutions must be complete to be successful.

  8. DIGITAL ERA: UTILIZE OF CLOUD COMPUTING TECHNOLOGY IN DIGITAL LIBRARY

    OpenAIRE

    T. RAGHUNADHA REDDY

    2012-01-01

    With the purpose of applying cloud computing to digital library, the paper initially describes cloud computing and analyzes current status of cloud computing in digital library. Then it proposes the architecture of cloud computing in digital library and summarises the application of cloud computing in digital library. Finally the author brings out the future improvement in digital library using cloud computing technology.

  9. Digital Natives and Digital Divide: Analysing Perspective for Emerging Pedagogy

    Science.gov (United States)

    Onye, Uriel U.; Du, Yunfei

    2016-01-01

    This paper addresses the concepts of digital natives and digital divide from the perspective of the digital outsiders (part of digital natives). It takes a critical look at the implications of available ICT in both developed and underdeveloped countries in the fight against digital divide. The major contribution to literature is by drawing…

  10. 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

  11. Digital Technology Entrepreneurship

    DEFF Research Database (Denmark)

    Giones, Ferran; Brem, Alexander

    2017-01-01

    Technology entrepreneurship is an established concept in academia. However, recent developments in the context of digital entrepreneurship call for revision and advance- ment. The multiple possible combinations of technology and entrepreneurship have res- ulted in a diversity of phenomena...... with significantly different characteristics and socio-economic impact. This article is focused on the identification and description of technology entrepreneurship in times of digitization. Based on current examples, we identify and describe characterizations of technology entrepreneurship, digital techno- logy...

  12. Digital Sensor Technology

    Energy Technology Data Exchange (ETDEWEB)

    Thomas, Ken D. [Idaho National Lab. (INL), Idaho Falls, ID (United States); Quinn, Edward L. [Technology Resources, Dana Point, CA (United States); Mauck, Jerry L. [Technology Resources, Dana Point, CA (United States); Bockhorst, Richard M. [Technology Resources, Dana Point, CA (United States)

    2015-02-01

    The nuclear industry has been slow to incorporate digital sensor technology into nuclear plant designs due to concerns with digital qualification issues. However, the benefits of digital sensor technology for nuclear plant instrumentation are substantial in terms of accuracy and reliability. This paper, which refers to a final report issued in 2013, demonstrates these benefits in direct comparisons of digital and analog sensor applications. Improved accuracy results from the superior operating characteristics of digital sensors. These include improvements in sensor accuracy and drift and other related parameters which reduce total loop uncertainty and thereby increase safety and operating margins. An example instrument loop uncertainty calculation for a pressure sensor application is presented to illustrate these improvements. This is a side-by-side comparison of the instrument loop uncertainty for both an analog and a digital sensor in the same pressure measurement application. Similarly, improved sensor reliability is illustrated with a sample calculation for determining the probability of failure on demand, an industry standard reliability measure. This looks at equivalent analog and digital temperature sensors to draw the comparison. The results confirm substantial reliability improvement with the digital sensor, due in large part to ability to continuously monitor the health of a digital sensor such that problems can be immediately identified and corrected. This greatly reduces the likelihood of a latent failure condition of the sensor at the time of a design basis event. Notwithstanding the benefits of digital sensors, there are certain qualification issues that are inherent with digital technology and these are described in the report. One major qualification impediment for digital sensor implementation is software common cause failure (SCCF).

  13. Preserving Digital Materials

    CERN Document Server

    Harvey, Ross

    2011-01-01

    This book provides a single-volume introduction to the principles, strategies and practices currently applied by librarians and recordkeeping professionals to the critical issue of preservation of digital information. It incorporates practice from both the recordkeeping and the library communities, taking stock of current knowledge about digital preservation and describing recent and current research, to provide a framework for reflecting on the issues that digital preservation raises in professional practice.

  14. The digital computer

    CERN Document Server

    Parton, K C

    2014-01-01

    The Digital Computer focuses on the principles, methodologies, and applications of the digital computer. The publication takes a look at the basic concepts involved in using a digital computer, simple autocode examples, and examples of working advanced design programs. Discussions focus on transformer design synthesis program, machine design analysis program, solution of standard quadratic equations, harmonic analysis, elementary wage calculation, and scientific calculations. The manuscript then examines commercial and automatic programming, how computers work, and the components of a computer

  15. Digital collections and exhibits

    CERN Document Server

    Denzer, Juan

    2015-01-01

    Today's libraries are taking advantage of cutting-edge technologies such as flat panel displays using touch, sound, and hands-free motions to design amazing exhibits using everything from simple computer hardware to advanced technologies such as the Microsoft Kinect. Libraries of all types are striving to add new interactive experiences for their patrons through exciting digital exhibits, both online and off. Digital Collections and Exhibits takes away the mystery of designing stunning digital exhibits to spotlight library trea

  16. Debunking the "Digital Native": Beyond Digital Apartheid, towards Digital Democracy

    Science.gov (United States)

    Brown, C.; Czerniewicz, L.

    2010-01-01

    This paper interrogates the currently pervasive discourse of the "net generation" finding the concept of the "digital native" especially problematic, both empirically and conceptually. We draw on a research project of South African higher education students' access to and use of Information and Communication Technologies (ICTs)…

  17. Digitally-Driven Architecture

    Directory of Open Access Journals (Sweden)

    Henriette Bier

    2010-06-01

    Full Text Available The shift from mechanical to digital forces architects to reposition themselves: Architects generate digital information, which can be used not only in designing and fabricating building components but also in embedding behaviours into buildings. This implies that, similar to the way that industrial design and fabrication with its concepts of standardisation and serial production influenced modernist architecture, digital design and fabrication influences contemporary architecture. While standardisa­tion focused on processes of rationalisation of form, mass-customisation as a new paradigm that replaces mass-production, addresses non-standard, complex, and flexible designs. Furthermore, knowledge about the designed object can be encoded in digital data pertaining not just to the geometry of a design but also to its physical or other behaviours within an environment. Digitally-driven architecture implies, therefore, not only digitally-designed and fabricated architecture, it also implies architecture – built form – that can be controlled, actuated, and animated by digital means. In this context, this sixth Footprint issue examines the influence of digital means as prag­matic and conceptual instruments for actuating architecture. The focus is not so much on computer-based systems for the development of architectural designs, but on architecture incorporating digital control, sens­ing, actuating, or other mechanisms that enable buildings to inter­act with their users and surroundings in real time in the real world through physical or sensory change and variation.

  18. The Digital Turn

    NARCIS (Netherlands)

    Westera, Wim

    2013-01-01

    Westera, W. (2013, 22 May). The Digital Turn. How the internet transforms our existence. Invited presentation at the symposium "Onderwijsvernieuwen in crisistijd", Heerlen, The Netherlands: Open Universiteit.

  19. Digital security technology simplified.

    Science.gov (United States)

    Scaglione, Bernard J

    2007-01-01

    Digital security technology is making great strides in replacing analog and other traditional security systems including CCTV card access, personal identification and alarm monitoring applications. Like any new technology, the author says, it is important to understand its benefits and limitations before purchasing and installing, to ensure its proper operation and effectiveness. This article is a primer for security directors on how digital technology works. It provides an understanding of the key components which make up the foundation for digital security systems, focusing on three key aspects of the digital security world: the security network, IP cameras and IP recorders.

  20. The digital media handbook

    CERN Document Server

    Dewdney, Andrew

    2013-01-01

    The new edition of The Digital Media Handbook presents an essential guide to the historical and theoretical development of digital media, emphasising cultural continuity alongside technological change, and highlighting the emergence of new forms of communication in contemporary networked culture.Andrew Dewdney and Peter Ride present detailed critical commentary and descriptive historical accounts, as well as a series of interviews from a range of digital media practitioners, including producers, developers, curators and artists.The Digital Media Handbook highlights key concerns of today's prac