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A new method for arbitrarily-oriented text detection in video

A new method for arbitrarily-oriented text detection in vide...

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10th IAPR International Workshop on Document Analysis Systems, DAS 2012

作者： Sharma, Nabin Shivakumara, Palaiahnakote Pal, Umapada Blumenstein, Michael Tan, Chew Lim Griffith University QLD Australia School of Computing National University of Singapore Singapore Singapore Computer Vision and Pattern Recognition Unit Indian Statistical Unit Kolkata India

ISBN: (纸本)9780769546612

Text detection in video frames plays a vital role in enhancing the performance of information extraction systems because the text in video frames helps in indexing and retrieving video efficiently and accurately. This paper presents a new method for arbitrarily-oriented text detection in video, based on dominant text pixel selection, text representatives and region growing. The method uses gradient pixel direction and magnitude corresponding to Sobel edge pixels of the input frame to obtain dominant text pixels. Edge components in the Sobel edge map corresponding to dominant text pixels are then extracted and we call them text representatives. We eliminate broken segments of each text representatives to get candidate text representatives. Then the perimeter of candidate text representatives grows along the text direction in the Sobel edge map to group the neighboring text components which we call word patches. The word patches are used for finding the direction of text lines and then the word patches are expanded in the same direction in the Sobel edge map to group the neighboring word patches and to restore missing text information. This results in extraction of arbitrarily-oriented text from the video frame. To evaluate the method, we considered arbitrarily-oriented data, non-horizontal data, horizontal data, Hua's data and ICDAR-2003 competition data (Camera images). The experimental results show that the proposed method outperforms the existing method in terms of recall and f-measure. © 2012 IEEE.

关键词： Pixels

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Off-line Bangla signature verification

Off-line Bangla signature verification

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10th IAPR International Workshop on Document Analysis Systems, DAS 2012

作者： Pal, Srikanta Nguyen, Vu Blumenstein, Michael Pal, Umapada School of Information and Communication Technology Griffith University Gold Coast QLD Australia Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata-700108 India

ISBN: (纸本)9780769546612

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. © 2012 IEEE.

关键词： Biometrics

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Lexicon reduction technique for Bangla handwritten word recognition

Lexicon reduction technique for Bangla handwritten word reco...

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10th IAPR International Workshop on Document Analysis Systems, DAS 2012

作者： Bhowmik, Tapan Kumar Roy, Utpal Parui, Swapan K. Faculty of Mathematics and Natural Sciences University of Groningen Netherlands Department of Computer and System Sciences Visva Bharati Santiniketan India Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India

ISBN: (纸本)9780769546612

In this paper we introduce a stroke based lexicon reduction technique in order to reduce the search space for recognition of handwritten words. The principle of this technique involves mainly two aspects of a word image to constitute a feature vector: one is word-length and the other is shape of the word. The length of the word image is represented by the number of specific vertical strokes present in the word image and, on the other hand, the shape of a word image is realized with the combination of both horizontal and vertical strokes. The experiment has been carried out with a database of 35,700 off-line handwritten Bangla word images. Though our proposed lexicon reduction technique is developed for recognition of Bangla handwritten words, its generalization property can easily be exploited for recognition of handwriting in other scripts also. © 2012 IEEE.

关键词： Character recognition

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A probabilistic framework for logo detection and localization in natural scene images

A probabilistic framework for logo detection and localizatio...

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International Conference on pattern recognition

作者： Ankush Roy Utpal Garain Computer Vision and Pattern Recognition Unit Indian Statistical Institute India

ISBN: (纸本)9781467322164

This paper presents a probabilistic approach for logo detection and localization in natural scene images. Two probability distributions are computed, one considering the features extracted from the key points located inside a region and the second refers to shape geometry defined by the key points. The barycentric co-ordinates are considered to define the shape statistics. The performance of the proposed approach has been reported on two publicly available datasets: BelgaLogos and Flickr Logos27. It is shown that statistically significant improvement is achieved over a recently proposed method.

关键词： Feature extraction Shape Geometry Accuracy Probabilistic logic Databases Visualization

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Anaphora Resolution in Bangla Using Global Discourse Knowledge

Anaphora Resolution in Bangla Using Global Discourse Knowled...

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International Conference on Asian Language Processing (IALP)

作者： Apurbalal Senapati Utpal Garain Computer Vision & Pattern Recognition Unit Indian Statistical Institute Kolkata India

This paper presents a pronominal anaphora resolution (PAR) approach that makes use of the global discourse knowledge along with other traditional features. So far the features used in finding the referent of an anaphoric pronoun are computed locally. Normally the sentence containing the anaphor and a few sentences immediately before form the local context. In this process, the knowledge base gets updated as more and more of the discourse is processed. Keeping this approach as the core, the present paper explores use of some prior knowledge after examining the entire discourse (whole article). Addition of this processing step improves the PAR's efficiency. This improvement is demonstrated using ICON 2011 Bangla dataset.

关键词： Pragmatics Natural language processing Organizations Communities computer vision pattern recognition Roads

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A System for Handwritten and Machine-Printed Text Separation in Bangla Document Images

A System for Handwritten and Machine-Printed Text Separation...

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International Workshop on Frontiers in Handwriting recognition

作者： Purnendu Banerjee B.B. Chaudhuri Indian Statistical Institute Computer Vision and Pattern Recognition Unit Kolkata India

In this paper, we describe an approach to distinguish between hand-written text and machine-printed text from annotated machine-printed Bangla Documents images. In applications involving OCR, distinction of machine-printed and hand-written characters is important, so that they can be sent to separate recognition engines. Identification of hand-written parts is useful in deleting those parts and cleaning the document image as well. In this paper a classification system is presented which takes a connected component in the document image and assigns them to two classes namely "machine-printed" and for "hand-written" classes, respectively. The proposed system contains a preprocessing step, which smoothes the object border and finds the Connected Component. Bangla script specific features are extracted from that Connected Component image, and a standard classifier based on SVM generates the final response. Experimental results on a data set show that the proposed approach achieves an overall accuracy of 96.49%.

关键词： Support vector machines Feature extraction Handwriting recognition Accuracy Text recognition Training

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Recent Advances in Video Based Document Processing: A Review

Recent Advances in Video Based Document Processing: A Review

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IAPR International Workshop on Document Analysis Systems, DAS

作者： Nabin Sharma Umapada Pal Michael Blumenstein Griffith University Queensland Australia Computer Vision and Pattern Recognition Unit Indian Statistical Unit Kolkata India

Extraction and recognition of text present in video has become a very popular research area in the last decade. Generally, text present in video frames is of different size, orientation, style, etc. with complex backgrounds, noise, low resolution and contrast. These factors make the automatic text extraction and recognition in video frames a challenging task. A large number of techniques have been proposed by various researchers in the recent past to address the problem. This paper presents a review of various state-of-the-art techniques proposed towards different stages (e.g. detection, localization, extraction, etc.) of text information processing in video frames. Looking at the growing popularity and the recent developments in the processing of text in video frames, this review imparts details of current trends and potential directions for further research activities to assist researchers.

关键词： Feature extraction Image edge detection Text recognition Support vector machines Character recognition Accuracy Optical character recognition software

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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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Stroke Segmentation and recognition from Bangla Online Handwritten Text

Stroke Segmentation and Recognition from Bangla Online Handw...

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International Workshop on Frontiers in Handwriting recognition

作者： Nilanjana Bhattacharya Umapada Pal Bose Institute Kolkata India Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India

This paper deals with recognition of online handwritten Bangla (Bengali) text. Here, at first, we segment cursive words into strokes. A stroke may represent a character or a part of a character. We selected a set of Bangla words written by different groups of people such that they contain all basic characters, all vowel and consonant modifiers and almost all types of possible joining among them. For segmentation of text into strokes, we discovered some rules analyzing different joining patterns of Bangla characters. Combination of online and offline information was used for segmentation. We achieved correct segmentation rate of 97.89% on the dataset. We manually analyzed different strokes to create a ground truth set of distinct stroke classes for result verification and we obtained 85 stroke classes. Directional features were used in SVM for recognition and we achieved correct stroke recognition rate of 97.68%.

关键词： Support vector machines Handwriting recognition Image segmentation Gold Writing Feature extraction Character recognition

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Effect of perceptual anchorage points on recognition of Bangla characters

Effect of perceptual anchorage points on recognition of Bang...

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1st Indo-Japan Conference on Perception and Machine Intelligence, PerMIn 2012

作者： Bandyopadhyay, Asok Mukherjee, Bhaswati Chaudhuri, Bidyut Baran Centre for Development of Advanced Computing Plot-E2/1 Block GP Salt Lake Kolkata-700091 India Computer Vision and Pattern Recognition Unit Indian Statistical Institute 203 B.T. Road Kolkata-700108 India

ISBN: (纸本)9783642273865

Character recognition (Printed and Handwritten) system has become an extremely useful tool in Human computer Interaction. Handwriting is a complex perceptual motor task generating linguistic information. Characters reflect shape distinction needed to perceive different phonetic information of words. We have explored 'perceptual processes' of character recognition for developing a cognitive model. Especially, we tried to extract the Perceptual Anchorage Points in the character. An experiment was performed to identify Perceptual anchorage points in a character both for handwritten as well as printed character of different Bangla script fonts including fonts used in Bangladesh. A set of important points and shapes has been found in the experiment. It is noted that deletion of these regions from characters greatly reduces the human cognition of characters. © 2012 Springer-Verlag.

关键词： Character recognition

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