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Erratum to “A cascaded genetic algorithm for efficient optimization and pattern matching” [Image and vision Computing 20(4) (2002) 265–277]

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Image and vision Computing 2002年第13-14期20卷 1017-1019页

作者： G Garai B.B Chaudhuri Computer Division Saha Institute of Nuclear Physics 1/AF Bidhannagar Calcutta 700 064 India Computer Vision and Pattern Recognition Unit Indian Statistical Institute 203 B.T. Road Calcutta 700 035 India

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Offline handwritten Devanagari word recognition: Information fusion at feature and classifier levels 3

Offline handwritten Devanagari word recognition: Information...

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3rd IAPR Asian Conference on pattern Recognition, ACPR 2015

作者： Shaw, Bikash Bhattacharya, Ujjwal Parui, Swapan Kumar Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata700108 India

ISBN: (纸本)9781479961009

This article presents our recent study on fusion of information at feature and classifier output levels for improved performance of offline handwritten Devanagari word recognition. We consider here two state-of-the-art features, viz., Directional Distance Distribution (DDD) and Gradient-Structural-Concavity (GSC) features along with multi-class SVM classifiers. Here, we study various combinations of DDD features along with one or more features from the GSC feature set. We experiment by presenting different combined feature vectors as input to SVM classifiers. Also, the output vectors of different SVM classifiers fed with different feature vectors are combined by another SVM classifier. The combination of the outputs of two SVMs each being fed with a different feature vector provides superior performance to the performance of a single SVM classifier fed with the combined feature vector. Experimental results are obtained on a large handwritten Devanagari word sample image database of 100 Indian town names. The recognition results on its test samples show that SVM recognition output of DDD features combined with the SVM output of GSC features improves the final recognition accuracy significantly. © 2015 IEEE.

关键词： Classification (of information)

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OCR error detection and correction of an inflectional Indian language script

OCR error detection and correction of an inflectional Indian...

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13th International Conference on pattern Recognition, ICPR 1996

作者： Chaudhuri, B.B. Pal, U. Computer Vision and Pattern Recognition Unit Indian Statistical Institute Calcutta 35 India

ISBN: (纸本)081867282X

This paper deals with an OCR error detection and correction technique for a highly inflectional language script like Bangla (a major Indian language). This is the first report of its kind. Using two separate lexicons of root words and suffixes, candidate root-suffix pairs of each input word are detected, their grammatical agreement are tested and the root/suffix part in which the error has occurred is noted. The correction is made on the corresponding error part of the input string by a fast dictionary access technique. To do so some alternative strings are generated for an erroneous word. Among the alternative strings, those satisfying grammatical agreement in root-suffix and also having smallest Levenstein-Damerau distance are finally chosen as the correct ones. The system has an accuracy of 75.61%. © 1996 IEEE.

关键词： Error detection

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A robust scheme for extraction of text lines from handwritten documents

A robust scheme for extraction of text lines from handwritte...

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International Conference on computer vision and Image Processing, CVIP 2016

作者： Biswas, Barun Bhattacharya, Ujjwal Chaudhuri, Bidyut B. Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata108 India

ISBN: (纸本)9789811021060

Considering the vast collection of handwritten documents in various archives, research studies for their automatic processing have major impact in the society. Line segmentation from images of such documents is a crucial step. The problem is more difficult for documents of major Indian scripts such as Bangla because a large number of its characters have either ascender or descender or both and the majority of its writers are accustomed in extremely cursive handwriting. In this article, we describe a novel strip based text line segmentation method for handwritten documents of ***, the proposed method has been found to perform efficiently on English and Devanagari handwritten *** conducted extensive experimentations and its results show the robustness of the proposed approach on multiple scripts. © Springer Science+Business Media Singapore 2017.

关键词： Image segmentation

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An MLP-based texture segmentation technique which does not require a feature set

An MLP-based texture segmentation technique which does not r...

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13th International Conference on pattern Recognition, ICPR 1996

作者： Bhattacharya, U. Chaudhuri, B.B. Parui, S.K. Computer Vision and Pattern Recognition Unit Indian Statistical Institute Calcutta - 35 India

ISBN: (纸本)081867282X

In this paper we describe a texture segmentation approach without feature computation based on a multilayer perceptron network (MLP). Thus, the users need not bother about the selection and then computation of feature set and hence real-time segmentation may be possible. The basic motivation of the work is the fact that human vision does not consciously compute features for distinguishing different textures in a scene. A single hidden layer MLP network has been found to be most suitable with heuristically chosen input and hidden layer sizes. A method has been used to speedup the learning of the MLP network. The result of segmentation by a trained network usually results in misclassification in the form of speckles. For the removal of such noise an edge-preserving-noise- smoothing technique is proposed. The final segmentation accuracy is well comparable with that of other existing techniques. © 1996 IEEE.

关键词： pattern recognition

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Writer Identification from offline isolated Bangla characters and numerals 13

Writer Identification from offline isolated Bangla character...

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13th International Conference on Document Analysis and Recognition, ICDAR 2015

作者： Adak, Chandranath Chaudhuri, Bidyut B. Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata700108 India

ISBN: (纸本)9781479918058

Writer identification is an essential component in computational forensic. In this paper, we attempt to do this job based only on isolated characters and numerals. For that, at first, some points of interest (keypoints) on the image are detected by structural analysis and SIFT based detector. Then we calculate a set of features within a certain neighborhood of the keypoint and employ fusion rule on multiple probabilistic SVM classifiers output for writer identification. For experimental analysis, a database containing 212,300 isolated Bangla orthosyllabic characters and numerals are generated with the help of 100 writers. We obtain fairly good result to identify a writer. We also try to find a small set of highly discriminative characters storing extra information about the writing style of an individual. © 2015 IEEE.

关键词： handwriting recognition natural language processing probability support vector machines Bangla orthosyllabic characters SIFT based detector computational forensic isolated Bangla characters isolated Bangla numerals isolated characters multiple probabilistic SVM classifiers structural analysis writer identification Chlorine Discriminative Bangla character Handwriting analysis Writer identification Numerals handwriting recognition structural analysis Structural analysis Support Vector Network Natural Language Processing Writers Chlorine

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Exemplary Sequence Cardinality: An effective application for word spotting 13

Exemplary Sequence Cardinality: An effective application for...

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13th International Conference on Document Analysis and Recognition, ICDAR 2015

作者： Mondal, Tanmoy Ragot, Nicolas Ramel, Jean-Yves Pal, Umapada France Indian Statistical Institute Computer Vision and Pattern Recognition Unit Kolkata India

ISBN: (纸本)9781479918058

In this paper proposed. ESC combines several abilities of other sequence matching algorithms e.g. DTW, SSDTW, CDP, FSM, MVM, OSB1. Depending on the application domain, ESC can be tuned to∗∗a new sequence matching algorithm called as Exemplary Sequence Cardinality (ESC) is behave such as these different sequence matching algorithms. Its generality and robustness comes from its ability to find subsequences (as in CDP and SSDTW), to skip outliers inside the target sequences (as in MVM and FSM) and also in the query sequence (as in OSB ) and it has the ability to have many to one and one to many correspondences (as in DTW) between the elements of the query and the target sequences. It's special characteristic of skipping noisy elements from query sequence along with other afore mentioned properties gives it an edge over FSM. In case of word spotting application, the outliers skipping capability of ESC makes it less sensible to local variations in the spelling of words, and also to noise present in the query and/or in the target word images. Due to it's capability of sub-sequence matching, the ESC algorithm has the ability to retrieve a query inside a line or piece of line. Finally, its multiple matching facilities (many to one and one to many matching) is proven to be well advantageous in case of different length of target and query sequences due to the variability in scale, font, type/size factors. By experimenting on printed historical document images, we have demonstrated the interest of proposed ESC algorithm in specific cases when incorrect word segmentation and word level local variations occur regularly. © 2015 IEEE.

关键词： Dynamic programming

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Devanagari and Bangla text extraction from natural scene images

Devanagari and Bangla text extraction from natural scene ima...

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ICDAR2009 - 10th International Conference on Document Analysis and Recognition

作者： Bhattacharya, U. Parui, S.K. Mondal, S. Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata - 108 India

ISBN: (纸本)9780769537252

With the increasing popularity of digital cameras attached with various handheld devices, many new computational challenges have gained significance. One such problem is extraction of texts from natural scene images captured by such devices. The extracted text can be sent to OCR or to a text-to-speech engine for recognition. In this article, we propose a novel and effective scheme based on analysis of connected components for extraction of Devanagari and Bangla texts from camera captured scene images. A common unique feature of these two scripts is the presence of headline and the proposed scheme uses mathematical morphology operations for their extraction. Additionally, we consider a few criteria for robust filtering of text components from such scene images. Moreover, we studied the problem of binarization of such scene images and observed that there are situations when repeated binarization by a well-known global thresholding approach is effective. We tested our algorithm on a repository of 100 scene images containing texts of Devanagari and / or Bangla © 2009 IEEE.

关键词： Extraction

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Low Resource Degraded Quality Document Image Binarization - Domain Adaptation is the Way 13

Low Resource Degraded Quality Document Image Binarization - ...

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13th Indian Conference on computer vision, Graphics, and Image Processing, ICVGIP 2022

作者： Kundu, Ahana Bhattacharya, Ujjwal Computer Vision and Pattern Recognition Indian Statistical Institute West Bengal Kolkata India

ISBN: (纸本)9781450398237

Usually, image binarization plays a crucial role in automatic analysis of degraded documents from their captured images. However, this binarization task is often difficult due to a number of reasons including the high similarity between noisy background and faded foreground pixels. The study presented here is particularly focused on binarization of images of low-resource degraded quality documents based on a set of recently collected image samples of several rare, ancient and severely degraded quality printed documents of Bangla, the 2nd and 5th most popular script of India and the world respectively. This new collection of degraded document image samples will henceforth be referred as 'ISIDDI2' and it consists of 139 images of Bangla old document pages. Samples of 'ISIDDI', another existing database of degraded Bangla document image samples, have also been used in the present study. A novel deep architecture based on attention UNET++ with dilated convolution operation is proposed for this binarization task. The model is optimized using human vision perceptible distance reciprocal distortion (DRD) loss. Since the binarization ground truth of samples of both 'ISIDDI2' and 'ISIDDI' are not available, the proposed network has been trained using samples of DIBCO and H-DIBCO datasets and an unsupervised domain adaptation (DA) module is employed for adaptation of the proposed architecture to the degradation patterns of 'ISIDDI2' or 'ISIDDI' samples. The proposed binarization strategy includes certain post-processing operation based on a modified k-neighbourhood based approach for recovery of broken characters. Results of our extensive experimentation show that the proposed binarization strategy has improved the binarization output of state-of-the-art methods on both ISIDDI2 and ISIDDI datasets. Also, its performance on well-known DIBCO samples is satisfactory. © 2022 ACM.

关键词： Network architecture

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Performance evaluation of DTW and its variants for word spotting in degraded documents 13

Performance evaluation of DTW and its variants for word spot...

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13th International Conference on Document Analysis and Recognition, ICDAR 2015

作者： Mondal, Tanmoy Ragot, Nicolas Ramel, Jean-Yves Pal, Umapada Tours France Indian Statistical Institute Computer Vision and Pattern Recognition Unit Kolkata India

ISBN: (纸本)9781479918058

In word spotting literature, classical DTW has been widely employed. However there exists several other improved versions of DTW along with other robust sequence matching techniques. Very few of them have been studied in the context of word spotting and this scarcity of research work is the motivation of the paper. This paper presents a comparative study of classical Dynamic Time Warping (DTW) technique and many of its improved modifications, as well as other sequence matching techniques in the context of word spotting. An experimental study on historical documents is performed to evaluate the behavior of DTW's variants and other sequence matching techniques. A detailed comparative analysis along with wide range of experimentation is performed, which shows that classical DTW remains a good choice when there are no segmentation problems and when features are very local. In case of word segmentation errors, Continuous Dynamic Programming (CDP) seems to be a better choice. This research work has introduced several other improved sequence matching algorithms in the context of word spotting, which show interesting and improved results. © 2015 IEEE.

关键词： Dynamic programming

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