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Segmentation of coarticulated basic units in isolated Bangla words using multifactorial analysis

Segmentation of coarticulated basic units in isolated Bangla...

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IEEE India Conference (INDICON)

作者： T. Chattopadhyay B.B. Chaudhuri Systems TCS Kolkata India Computer Vision and Pattern Recognition Unit Indian Statistical Institute India

One of the major challenges in speech synthesis and recognition is coarticulated unit segmentation. In this paper we present a novel technique for segmenting the basic coarticulated units using multifactorial analysis based approach. The proposed algorithm is applied on isolated spoken words in Bangla. The results obtained from a considerably large database show the strength of the approach.

关键词： Speech synthesis State-space methods Databases Automatic speech recognition Image segmentation Image processing Linear predictive coding Switches Testing Signal analysis

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An approach for Bangla and Devanagari video text recognition 13

An approach for Bangla and Devanagari video text recognition

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4th International Workshop on Multilingual OCR, MOCR 2013

作者： Banerjee, Purnendu Chaudhuri, B.B. Society for Natural Language Technology Research Module 130 SDF Building Kolkata-700091 India Computer Vision and Pattern Recognition Unit Indian Statistical Institute 203 B. T. Road Kolkata- 108 India

ISBN: (纸本)9781450321143

Extraction and recognition of Bangla text from video frame images is challenging due to fonts type and style variation, complex color background, low-resolution, low contrast etc. In this paper, we propose an algorithm for extraction and recognition of Bangla and Devanagari text form video frames with complex background. Here, a two-step approach has been proposed. After text localization, the text line is segmented into words using information based on line contours. First order gradient values of the text blocks are used to find the word gap. Next, an Adaptive SIS binarization technique is applied on each word. Next this binarized text block is sent to a state of the art OCR for recognition. © 2013 ACM.

关键词： Extraction

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Preliminary Level Cardiac Abnormality Detection Using Wireless Telecardiology System

Preliminary Level Cardiac Abnormality Detection Using Wirele...

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International Conference on the Digital Society

作者： M. Mitra S. Mitra J.N. Bera R. Gupta B.B. Chaudhuri Department of Applied Physics University of Calcutta India Computer Vision and Pattern Recognition Unit Kolkata India

ISBN: (纸本)9781424431342;0769527604

This paper describes a portable diagnostic telecardiology system, aimed to benefit the rural people of a third world country like India. The designed system consists of two major blocks; the first one is required to be carried to the patient home, named 'Portable Telecardiology Kit'. The second one, named 'Automated Cardiac Signal Processor', a PC based system, to be permanently placed at the nearest rural health care center. The 'Portable Telecardiology Kit' contains a portable ECG machine, a dedicated microcontroller-based full duplex communication system, both interfaced, in a single enclosure. This kit will convert the ECG signal along with a tag page (containing different information regarding patient's health and history of illness) to a digitized serial electromagnetic wave. The signal may be transmitted over a distance of about 7-10 km through a cordless phone under full duplex mode. The PC-based system, after receiving the transmitted signal from patient site, extract the ECG signal after proper filtering, and then pass the signal through an in-built knowledge-base. Finally, a rule-based rough set decision system is generated for the development of an inference engine for disease identification from these time-plane features. The system will generate a report indicating the preliminary level abnormalities, and the precautions that can be adopted at an early stage. The entire report is then sent to the Portable kit at the patient bed-site.

关键词： Electrocardiography Telemedicine Medical services Artificial neural networks Set theory pattern recognition Fuzzy neural networks Diseases Discrete wavelet transforms Radiofrequency amplifiers

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Approximate Nearest Neighbour Search on Privacy-aware Encoding of User Locations to Identify Susceptible Infections in Simulated Epidemics 21

Approximate Nearest Neighbour Search on Privacy-aware Encodi...

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Proceedings of the 13th Annual Meeting of the Forum for Information Retrieval Evaluation

作者： Chandan Biswas Debasis Ganguly Ujjwal Bhattacharya Computer Vision and Pattern Recognition Unit Indian Statistical Institute India University of Glasgow United Kingdom

ISBN: (纸本)9781450395960

Amidst an increasing number of infected cases during the Covid-19 pandemic, it is essential to trace, as early as possible, the susceptible people who might have been infected by the disease due to their close proximity with people who were tested positive for the virus. This early contact tracing is likely to limit the rate of spread of the infection within a locality. In this paper, we investigate how effectively and efficiently can such a list of susceptible people be found given a list of infected persons and their locations. By using the locations of the given list of infected persons as queries, we investigate the feasibility of applying approximate nearest neighbour (ANN) based indexing and retrieval approaches to obtain a list of top-k suspected users in real-time. Since leveraging information from true user location data can lead to privacy concerns, we also investigate the effectiveness of the ANN methods on privacy-aware encoding of the input data. Experiments conducted on real and synthetic datasets demonstrate that the top-k susceptible users retrieved with existing ANN approaches (KD-tree and HNSW) yield satisfactory recall values and achieves up to 21000 × speed-gain compared to exhaustive search, thus indicating that ANN approaches can potentially be applied, in practice, to facilitate real-time contact tracing even under the presence of imposed privacy constraints.

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Multi-angle based lively sclera biometrics at a distance

Multi-angle based lively sclera biometrics at a distance

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2014 IEEE Symposium Series on Computational Intelligence, IEEE SSCI 2014 - 2014 IEEE Symposium on Computational Intelligence in Biometrics and Identity Management, CIBIM 2014

作者： Das, Abhijit Pal, Umapada Ballester, Miguel Angel Ferrer Blumenstein, Michael Institute for Integrated and Intelligent Systems Griffith University GriffithQLD Australia Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India IDeTIC University of Las Palmas de Gran Canaria Las Palmas Spain

ISBN: (纸本)9781479945344

This piece of work proposes a liveliness based sclera eye biometric, validation and recognition technique at a distance. The images in this work are acquired by a digital camera in the visible spectrum at varying distance of about 1 meter from the individual. Each individual during registration as well as validation is asked to look straight and move their eye ball up, left and right keeping their face straight to incorporate liveliness of the data. At first the image is divided vertically into two halves and the eyes are detected in each half of the face image that is captured, by locating the eye ball by a Circular Hough Transform. Then the eye image is cropped out automatically using the radius of the iris. Next a C-means-based segmentation is used for sclera segmentation followed by vessel enhancement by the adaptive histogram equalization and Haar filtering. The feature extraction was performed by patch-based Dense-LDP (Linear Directive pattern). Furthermore each training image is used to form a bag of features, which is used to produce the training model. Each of the images of the different poses is combined at the feature level and the image level to obtain higher accuracy and to incorporate liveliness. The fusion that produces the best result is considered. Support Vector Machines (SVMs) are used for classification. Here images from 82 individuals (both left and right eye i.e. 164 different eyes) are used and an appreciable Equal Error Rate of 0.52% is achieved in this work. © 2014 IEEE.

关键词： Support vector machines

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recognition of handprinted bangla numerals using neural network models 5th

引用

5th International Conference on Asian Fuzzy Systems Society, AFSS 2002

作者： Bhattacharya, U. Das, T.K. Datta, A. Parui, S.K. Chaudhuri, B.B. Computer Vision and Pattern Recognition Unit Indian Statistical Institute 203 B. T. Road Calcutta35 India Computer and Statistical Service Center Indian Statistical Institute 203 B. T. Road Calcutta35 India

ISBN: (纸本)9783540431503

This paper proposes an automatic recognition scheme for hand printed Bangla (an Indian script) numerals using neural network models. A Topology Adaptive Self Organizing Neural Network is first used to extract from a numeral pattern a skeletal shape that is represented as a graph. Certain features like loops, junctions etc. present in the graph are considered to classify a numeral into a smaller group. If the group is a singleton, the recognition is done. Otherwise, multilayer perceptron networks are used to classify different numerals uniquely. The system is trained using a sample data set of 1880 numerals and we obtained 90.56% correct recognition rate on a test set of another 3440 samples. The proposed scheme is sufficiently robust with respect to considerable object noise. © Springer-Verlag Berlin Heidelberg 2002.

关键词： Neural network models

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A New Deep Fuzzy Based MSER Model for Multiple Document Images Classification 3rd

A New Deep Fuzzy Based MSER Model for Multiple Document Imag...

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3rd International Conference on pattern recognition and Artificial Intelligence, ICPRAI 2022

作者： Biswas, Kunal Shivakumara, Palaiahnakote Sivanthi, Sittravell Pal, Umapada Lu, Yue Liu, Cheng-Lin Ayub, Mohamad Nizam Bin Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India Faculty of Computer Science and Information Technology University of Malaya Kuala Lumpur Malaysia Shanghai Key Laboratory of Multidimensional Information Processing East China Normal University Shanghai China National Laboratory of Pattern Recognition Institute of Automation of Chinese Academy of Sciences Beijing China School of Artificial Intelligence University of Chinese Academy Beijing China

ISBN: (纸本)9783031090363

Understanding document images uploaded on social media is challenging because of multiple types like handwritten, printed and scene text images. This study presents a new model called Deep Fuzzy based MSER for classification of multiple document images (like handwritten, printed and scene text). The proposed model detects candidate components that represent dominant information irrespective of the type of document images by combining fuzzy and MSER in a novel way. For every candidate component, the proposed model extracts distance-based features which result in proximity matrix (feature matrix). Further, the deep learning model is proposed for classification by feeding input images and feature matrix as input. To evaluate the proposed model, we create our own dataset and to show effectiveness, the proposed model is tested on standard datasets. The results show that the proposed approach outperforms the existing methods in terms of average classification rate. © 2022, Springer Nature Switzerland AG.

关键词： Image classification

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recognition of Multi-oriented Touching Characters in Graphical Documents

Recognition of Multi-oriented Touching Characters in Graphic...

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Indian Conference on computer vision, Graphics & Image Processing (ICVGIP)

作者： Partha Pratim Roy Umapada Pal Josep Lladós Computer Vision Center Universitat Autònoma Barcelona Bellaterra Spain Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India

Touching characters are major problem of achieving higher recognition rate in optical character recognition (OCR). Present OCR systems do not perform well when adjacent characters touch. If characters are touched in graphical documents (e.g. map) then such touching string recognition is more difficult because in such documents touching characters appear in multi-oriented direction. In this paper, we present a scheme towards the recognition of English two-character multi-oriented touching strings. When two or more characters touch, they generate a big cavity region at the background portion and we used this background information in our scheme. To handle the background information, convex hull is used. In this scheme, at first, a set of initial segmentation points is predicted based on the concave residues of the convex hull of the touching characters. Next, based on the initial points, we select some candidate segmentation lines. Finally the recognition confidence of two sub-images of a touching string, obtained from each candidate segmentation line is computed. The candidate segmentation line from which we get optimum confidence is the actual segmentation line and the corresponding characters in favour of which the two segmentation parts show optimum confidence is the recognition result of the touching string. To compute the recognition confidence, SVM classifier is used. The features used in the SVM are invariant to character orientation. Circular ring and convex hull ring based approach has been used along with angular information of the contour pixels of the character to make the feature rotation invariant. From the experiment we obtained encouraging result.

关键词： Character recognition Optical character recognition software pattern recognition Support vector machines Support vector machine classification Image segmentation Frequency Image recognition Character generation Degradation

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Off-line English and Chinese Signature Identification Using Foreground and Background Features

Off-line English and Chinese Signature Identification Using ...

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International Joint Conference on Neural Networks

作者： Srikanta Pal Umapada Pal Michael Blumenstein School of Information and Communication Technology Griffith University Computer Vision and Pattern Recognition Unit Indian Statistical Institute

ISBN: (纸本)9781467314886

In the field of information security, the usage of biometrics is growing for user authentication. Automatic signature recognition and verification is one of the biometric techniques, which is only one of several used to verify the identity of individuals. In this paper, a foreground and background based technique is proposed for identification of scripts from bi-lingual (English/Roman and Chinese) off-line signatures. This system will identify whether a claimed signature belongs to the group of English signatures or Chinese signatures. The identification of signatures based on its script is a major contribution for multi-script signature verification. Two background information extraction techniques are used to produce the background components of the signature images. Gradient-based method was used to extract the features of the foreground as well as background components. Zernike Moment feature was also employed on signature samples. Support Vector Machine (SVM) is used as the classifier for signature identification in the proposed system. A database of 1120 (640 English+480 Chinese) signature samples were used for training and 560 (320 English+240 Chinese) signature samples were used for testing the proposed system. An encouraging identification accuracy of 97.70% was obtained using gradient feature from the experiment.

关键词： Off-line verification systems Signature identification Biometrics Authentication systems SVM

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Off-line Handwritten Thai Name recognition for Student Identification in an Automated Assessment System

Off-line Handwritten Thai Name Recognition for Student Ident...

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International Joint Conference on Neural Networks

作者： Hemmaphan Suwanwiwat Vu Nguyen Michael Blumenstein Umapada Pal School of Information and Communication Technology Griffith University Computer Vision and Pattern Recognition Unit Indian Statistical Institute

ISBN: (纸本)9781479914821

In the field of pattern recognition, off-line handwriting recognition is one of the most intensive areas of study. This paper proposes an automatic off-line Thai language student name identification system which was built as a part of a completed off-line automated assessment system. There is limited work undertaken in developing off-line automatic assessment systems using handwriting recognition. To the authors' knowledge, none of the work on the proposed system has been performed on the Thai language. In addition the proposed system recognises each Thai name by using an approach for whole word recognition, which is different from the work found in the literature as most perform character-based recognition. In this proposed system, the Gaussian Grid Feature (GGF) and the Modified Direction Feature (MDF) extraction techniques are investigated on upper and lower contours, loops from full word contour images of each name sample, and artificial neural networks and support vector machine are used as classifiers. The encouraging recognition rates for both feature extraction techniques were achieved when applied on loop, upper and lower contour images (99.27% accuracy rate was achieved using MDF on artificial neural networks and 99.27% using GGF with a support vector machine classifier).

关键词： Off-line handwriting recognition Automated assessment system Student identification system Modified directional feature Gaussian grid feature

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