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A novel approach to skew detection and character segmentation for handwritten bangla words

A novel approach to skew detection and character segmentatio...

引用

Digital Imaging Computing: Techniques and Applications, DICTA 2005

作者： Roy, A. Bhowmik, T.K. Parui, S.K. Roy, U. Dept. of Computer and System Sciences Visva-Bharati Santiniketan 731235 India IBM Global Services Pvt. Ltd. Embassy Golf Link Bangalore - 560 071 India Computer Vision and Pattern Recognition Unit Indian Statistical Institute 203 B. T. Road Kolkata-700 108 India

ISBN: (纸本)0769524672

Character segmentation is a necessary preprocessing step for character recognition in many handwritten word recognition systems. The most difficult case in character segmentation is the cursive script. Fully cursive nature of Bangla handwriting, the natural skewness in words poses some challenges for automatic character segmentation. In this article a novel approach to skew detection, correction as well as character segmentation has been presented for handwritten Bangla words as a test case. Segmenting points are extracted on the basis of some patterns observed in the handwritten words. With these segmenting points a graphical path (hereafter referred to as a candidate path) has been constructed. The handwritten words contain some consistent and also inconsistent skewness. Our algorithm can cope with both types of skewness at a time. Further the method is so direct that with the help of a candidate path one can handle both skew correction and segmentation successfully, the algorithm has been tested on a database prepared for laboratory use. The method yields fairly good results for this database. © 2005 IEEE.

关键词： Image segmentation

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Word-Wise Handwriting Based Gender Identification Using Multi-Gabor Response Fusion 4th

Word-Wise Handwriting Based Gender Identification Using Mult...

引用

4th Workshop on Document Analysis and recognition, DAR 2018, held in Conjunction with the 11th Indian Conference on vision, Graphics, and Image Processing, ICVGIP 2018

作者： Asadzadeh Kaljahi, Maryam Vidya Varshini, P.V. Shivakumara, Palaiahnakote Pal, Umapada Lu, Tong Guru, D.S. Faculty of Computer Science and Information Technology University of Malaya Kuala Lumpur Malaysia Vellore Institute of Technology VelloreTamil Nadu India Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India National Key Lab for Novel Software Technology Nanjing University Nanjing China Department of Studies in Computer Science Manasagangotri University of Mysuru Mysore India

ISBN: (纸本)9789811393600

Handwriting based gender identification at the word level is challenging due to free style writing, use of different scripts, and inadequate information. This paper presents a new method based on Multi-Gabor Response (MGR) fusion for gender identification at the word level. It first explores weighted-gradient features for word segmentation from text line images. For each word, the proposed method obtains eight Gabor response images. Then it performs sliding window operation over MGR images to smooth the values. For each smoothed MGR images, we perform fusion operation that chooses the Gabor response value which contributes to the highest peak in the histogram. This process results in a feature matrix, which is fed to CNN for gender identification. Experimental results on our dataset (multi scripts) apart from English, and benchmark databases, namely, IAM, KHATT, and QUWI, which contain handwritten English and Arabic text, show that the proposed method outperforms the existing methods. © Springer Nature Singapore Pte Ltd. 2019.

关键词： Image segmentation

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A Statistics and Local Homogeneity Based Color Edge Detection Algorithm

A Statistics and Local Homogeneity Based Color Edge Detectio...

引用

International Conference on Advances in Recent Technologies in Communication and Computing, ARTCom

作者： Soumya Dutta Bidyut B. Chaudhuri Department of Electronics and Communication Netaji Subhash Engineering College Kolkata India Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India

Edge detection is one of the most commonly used operations in image processing and pattern recognition, the reason for this is that edges form the outline of an object. An edge is the boundary between an object and the background, and indicates the boundary between overlapping objects. This means that if the edges in an image can be identified accurately, all of the objects can be located and basic properties such as area, perimeter, and shape can be measured. Since computer vision involves the identification and classification of objects in an image, edge detection is an essential tool. Efficient and accurate edge detection will lead to increase the performance of subsequent image processing techniques, including image segmentation, object-based image coding, and image retrieval. A novel color edge detection algorithm is proposed in this paper. On the basis of standard deviation calculation of pixels the discontinuity among the pixels are detected. Then the image is segmented into a binary image with a fixed threshold where black pixels signify homogeneous region and white pixels signify edges. Finally, a thinning technique is applied to extract thin edges. The proposed method is applied over large database of color images both synthetic and real life images and performance of the algorithm is evident from the results and is comparable with other edge detection algorithms.

关键词： Statistics Image edge detection Image processing Object recognition Shape measurement Image segmentation Pixel pattern recognition Area measurement computer vision

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International Conference on pattern recognition

作者： Anjan Dutta Umapada Pal Josep Lladós Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India Computer Science Dept. Universitat Autònoma de Barcelona Bellaterra Spain

ISBN: (纸本)9781509048489

This paper considers the offline signature verification problem which is considered to be an important research line in the field of pattern recognition. In this work we propose hybrid features that consider the local features and their global statistics in the signature image. This has been done by creating a vocabulary of histogram of oriented gradients (HOGs). We impose weights on these local features based on the height information of water reservoirs obtained from the signature. Spatial information between local features are thought to play a vital role in considering the geometry of the signatures which distinguishes the originals from the forged ones. Nevertheless, learning a condensed set of higher order neighbouring features based on visual words, e.g., doublets and triplets, continues to be a challenging problem as possible combinations of visual words grow exponentially. To avoid this explosion of size, we create a code of local pairwise features which are represented as joint descriptors. Local features are paired based on the edges of a graph representation built upon the Delaunay triangulation. We reveal the advantage of combining both type of visual codebooks (order one and pairwise) for signature verification task. This is validated through an encouraging result on two benchmark datasets viz. CEDAR and GPDS300.

关键词： Feature extraction Reservoirs Histograms Visualization Forgery

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Hindi Off-Line Signature Verification

Hindi Off-Line Signature Verification

引用

International Workshop on Frontiers in Handwriting recognition

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

Handwritten Signatures are one of the widely used biometrics for document authentication as well as human authorization. The purpose of this paper is to present an off-line signature verification system involving Hindi signatures. Signature verification is a process by which the questioned signature is examined in detail in order to determine whether it belongs to the claimed person or not. Despite of substantial research in the field of signature verification involving Western signatures, very little attention has been dedicated to non-Western signatures such as Chinese, Japanese, Arabic, Persian etc. In this paper, the performance of an off-line signature verification system involving Hindi signatures, whose style is distinct from Western scripts, has been investigated. The gradient and Zernike moment features were employed and Support Vector Machines (SVMs) were considered for verification. To the best of the authors' knowledge, Hindi signatures have never been used for the task of signature verification and this is the first report of using Hindi signatures in this area. The Hindi signature database employed for experimentation consisted of 840 (35×24) genuine signatures and 1050 (35×30) forgeries. An encouraging accuracy of 7.42% FRR and 4.28% FAR were obtained following experimentation when the gradient features were employed.

关键词： Feature extraction Forgery Databases Support vector machines Training Testing

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Duplicate open page removal from video stream of book flipping

Duplicate open page removal from video stream of book flippi...

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National Conference on computer vision, pattern recognition, Image Processing and Graphics (NCVPRIPG)

作者： Dibyayan Chakraborty Partha Pratim Roy Jose M. Alvarez Umapada Pal Department of computer Science Ramakrishna Mission Vivekananda University Howrah India Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India NICTA Australia

Book flipping scanning refers to the process of recording a book while the user performs the flipping action of its pages. In recent years it has gained much attention as it reduces the workload of book digitization significantly. It is a challenging task because flipping at random speed and direction causes difficulties to identify distinct open page images (OPI) which represent each page of the book. In this paper, we propose a fast technique for removing duplicate open pages introduced in the video stream due to erroneous flipping. We present an algorithm that exploits cues from edge information of flipping pages. The nature of the cues extracted from the region of interest (ROI) of the frame, determines the flipping or an open state of a page whereas temporal position a flipping page determines the direction of the flipping. Combining these information we decide whether an open page image is a duplicate or not. Experiments are performed on video documents recorded using a standard resolution camera to validate the duplicate open page removal algorithm and we have obtained 95% accuracy.

关键词： Streaming media Feature extraction Cameras Optical character recognition software Image edge detection Accuracy Performance evaluation

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A Color Edge Detection Algorithm in RGB Color Space

A Color Edge Detection Algorithm in RGB Color Space

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International Conference on Advances in Recent Technologies in Communication and Computing, ARTCom

ISBN: (纸本)9781424451043

Edge detection is one of the most commonly used operations in image processing and pattern recognition, the reason for this is that edges form the outline of an object. An edge is the boundary between an object and the background, and indicates the boundary between overlapping objects. This means that if the edges in an image can be identified accurately, all of the objects can be located and basic properties such as area, perimeter, and shape can be measured. Since computer vision involves the identification and classification of objects in an image, edge detection is an essential tool. Efficient and accurate edge detection will lead to increase the performance of subsequent image processing techniques, including image segmentation, object-based image coding, and image retrieval. A color image edge detection algorithm is proposed in this paper. Average maximum color difference value is used to predict the optimum threshold value for a color image and thinning technique is applied to extract proper edges. The proposed method is applied over large database of color images both synthetic and real life images and performance of the algorithm is evident from the results and is comparable with other edge detection algorithms.

关键词： Image edge detection Color Image processing Object recognition Shape measurement pattern recognition Area measurement computer vision Image segmentation Image coding

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Mash up of Breaking News and Contextual Web Information: A Novel Service for Connected Television

Mash up of Breaking News and Contextual Web Information: A N...

引用

International Conference on computer Communications and Networks (ICCCN)

作者： T. Chattopadhyay Arpan Pal Utpal Garain Innovation Laboratory Tata Consultancy Services Limited Kolkata India Computer Vision and Pattern Recognition Unit Tata Consultancy Services Limited Kolkata India

The Connected TV can be described as an Internet enabled TV. In the current paper we have proposed a system for connected TV that mash up the information from internet and RSS feeds related to the breaking news aired over the TV. The proposed system initially localize the text regions from the streamed video in hybrid mode, then recognize them and spot the key words and finally fetch the related information from Internet. Our experimental results show that the localization of the text regions from the video can work with no misses but have some false positives which are taken care by data semantic analysis. The errors of the Optical Character recognition (OCR) module are taken care by using string comparing techniques like longest common subsequence matching and Leveinsthein distance while matching with the RSS feed or internet.

关键词： TV Internet Optical character recognition software Pixel Feeds Accuracy Noise

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A Weighted Finite-State Transducer (WFST)-Based Language Model for Online Indic Script Handwriting recognition

A Weighted Finite-State Transducer (WFST)-Based Language Mod...

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International Conference on Document Analysis and recognition

作者： Suhan Chowdhury Utpal Garain Tanushyam Chattopadhyay Computer Vision & Pattern Recognition (CVPR) Unit Indian Statistical Institute Kolkata India Innovation Laboratory Kolkata Tata Consultancy Services Kolkata India

Though designing of classifies for Indic script handwriting recognition has been researched with enough attention, use of language model has so far received little exposure. This paper attempts to develop a weighted finite-state transducer (WFST) based language model for improving the current recognition accuracy. Both the recognition hypothesis (i.e. the segmentation lattice) and the lexicon are modeled as two WFSTs. Concatenation of these two FSTs accept a valid word(s) which is (are) present in the recognition lattice. A third FST called error FST is also introduced to retrieve certain words which were missing in the previous concatenation operation. The proposed model has been tested for online Bangla handwriting recognition though the underlying principle can equally be applied for recognition of offline or printed words. Experiment on a part of ISI-Bangla handwriting database shows that while the present classifiers (without using any language model) can recognize about 73% word, use of recognition and lexicon FSTs improve this result by about 9% giving an average word-level accuracy of 82%. Introduction of error FST further improves this accuracy to 93%. This remarkable improvement in word recognition accuracy by using FST-based language model would serve as a significant revelation for the research in handwriting recognition, in general and Indic script handwriting recognition, in particular.

关键词： Handwriting recognition Hidden Markov models Character recognition Optical character recognition software Accuracy Transducers Vocabulary

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Off-Line Bangla Signature Verification

Off-Line Bangla Signature Verification

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IAPR International Workshop on Document Analysis Systems, DAS

作者： Srikanta Pal Vu Nguyen Michael Blumenstein Umapada Pal School of Information and Communication Technology Griffith University Gold Coast Australia Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India

In the field of information security, biometric systems play an important role. Within biometrics, automatic signature identification and verification has been a strong research area because of the social and legal acceptance and extensive use of the written signature as an individual authentication. Signature verification is a process in which the questioned signature is examined in detail in order to determine whether it belongs to the claimed person or not. Despite substantial research in the field of signature verification involving Western signatures, very few works have been dedicated to non-Western signatures such as Chinese, Japanese, Arabic, or Persian etc. In this paper, the performance of an off-line signature verification system involving Bangla signatures, whose style is distinct from Western scripts, was investigated. The Gaussian Grid feature extraction technique was employed for feature extraction and Support Vector Machines (SVMs) were considered for classification. The Bangla signature database employed in the experiments consisted of 3000 forgeries and 2400 genuine signatures. An encouraging accuracy of 90.4% was obtained from the experiments.

关键词： Forgery Feature extraction Support vector machines Databases Training Educational institutions

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