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Automatic separation of machine-printed and hand-written text lines 5

Automatic separation of machine-printed and hand-written tex...

引用

5th International Conference on Document Analysis and recognition, ICDAR 1999

作者： Pal, U. Chaudhuri, B.B. Computer Vision and Pattern Recognition Unit Indian Statistical Institute 203 B. T. Road Calcutta700 035 India

ISBN: (纸本)0769503187

There are many types of documents where machine-printed and hand-written texts appear intermixed. Since the optical character recognition (OCR) methodologies for machine-printed and hand-written texts are different, it is necessary to separate these two types of text before feeding them to the respective OCR systems. In this paper, we present such a scheme for both Bangla and Devnagari characters. The scheme is based on the structural and statistical features of the machine-printed and hand-written text lines. The classification scheme has an accuracy of about 98.3%. © 1999 IEEE.

关键词： Optical character recognition

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Document-zone classification in torn documents

Document-zone classification in torn documents

引用

International Conference on Frontiers in Handwriting recognition

作者： Chanda, Sukalpa Franke, Katrin Pal, Umapada Dept. of Computer Science and Media Technology Gjøvik University College Norway Computer Vision and Pattern Recognition Unit Indian Statistical Institute India

ISBN: (纸本)9780769542218

Arbitrary orientation and sparse data content are common characteristics of torn document. To ensure accuracy and reliability in computer-based analysis, content-zone segmentation is required. In our previous work, we studied segmentation of handwritten and printed text. A questioned document-piece in the form of an office note, however, might also contain non-text data like logos, graphics, and pictures. Hence a more precise content-zone classification is required. In this paper we propose a two-Tier approach for non-text, handwriting and printed text segmentation. The first Tier aims to discriminate text and non-text regions. The second Tier classifies handwritten and printed text within all text zones identified during the first Tier. Gabor features and chain-code features are used in Tier-1 and Tier-2, respectively. By using SVM classifier we successfully identified 97.65% of 31,227 text regions in our current test data. The proposed approach identified 98.69% of printed and 96.39% of handwritten text amongst all identified text regions. © 2010 IEEE.

关键词： Text processing

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On OCR of degraded documents using fuzzy multifactorial analysis 5th

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

作者： Garain, U. Chaudhuri, B.B. Computer Vision and Pattern Recognition Unit Indian Statistical Institute 203 B. T. Road Kolkata700 035 India

ISBN: (纸本)9783540431503

Optical Character recognition (OCR) systems show poor performance while processing documents like old books or newspapers, Xerox materials, faxed documents, etc. Such documents are considered as degraded documents. One of the important reasons for poor recognition rate for degraded documents is existence of touching or connected characters, which create a major problem for designing an effective character segmentation procedure. In this paper, a new technique is proposed for segmentation of touching characters. The technique is based on fuzzy multifactorial analysis. A predictive algorithm is developed for effectively selecting cut-points to segment touching characters. Initially, our proposed method has been applied for segmenting touching characters that appear in Devnagari (Hindi) and Bangla, two major scripts in Indian sub-continent. The results obtained from a test-set of considerable size show that a high recognition rate can be achieved with a reasonable amount of computations. © Springer-Verlag Berlin Heidelberg 2002.

关键词： Optical character recognition

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An approach for processing mathematical expressions in printed document 3rd

An approach for processing mathematical expressions in print...

引用

3rd IAPR Workshop on Document Analysis Systems, DAS 1998

作者： Chaudhuri, B.B. Gamin, U. Computer Vision and Pattern Recognition Unit Indian Statistical Institute 203 B. T. Road Calcutta700 035 India

ISBN: (纸本)3540665072

In this paper, we propose an approach for understanding mathematical expressions in printed document. The system consists of three main components namely (i) detection of mathematical expressions in a document, (ii) recognition of the symbols present in the expression and (iii) meaningful arrangement of the recognized symbols. However, detection of mathematical expressions is done through recognition of symbols. Moreover, some structural features of the expressions are also used for this purpose. For recognition of the symbols a hybrid of feature based and template based recognition techniques is used. The bounding-box coordinates and the size information of the symbols help to determine the spatial relationships among the symbols. A set of predefined grammar rules is used to form the meaningful symbol groups to properly arrange the symbols. Experiments conducted using these approaches on a large number of documents show high accuracy. © Springer-Verlag Berlin Heidelberg 1999.

关键词： computers

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Word–wise script identification from indian documents

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6th IAPR International Workshop on Document Analysis Systems, DAS 2004

作者： Sinha, Suranjit Pal, Umapada Chaudhuri, B.B. Computer Vision and Pattern Recognition Unit Indian Statistical Unit 203 B.T. Road Kolkata700 108 India

ISBN: (纸本)3540230602

In a country like India, a single text line of most of the official documents contains two different script words. Under two-language formula, the Indian documents are written in English and the state official language. For Optical Character recognition (OCR) of such a document page, it is necessary to separate different script words before feeding them to the OCRs of individual scripts. In this paper a robust technique is proposed to extract word-wise script identification from Indian doublet form documents. Here, at first, the document is segmented into lines and then the lines are segmented into words. Using different topological and structural features (like number of loops, headline feature, water reservoir concept based features, profile features, etc.) individual script words are identified from the documents. The proposed scheme is tested on 24210 words of different doublets and we received more than 97% accuracy, on average. © Springer-Verlag Berlin Heidelberg 2004.

关键词： Optical character recognition

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Text detection of two major Indian scripts in natural scene images

Text detection of two major Indian scripts in natural scene ...

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4th International Workshop on Camera-Based Document Analysis and recognition, CBDAR 2011

作者： Roy Chowdhury, Aruni Bhattacharya, Ujjwal Parui, Swapan K. Department of Information Technology Heritage Institute of Technology Kolkata India Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India

ISBN: (纸本)9783642293634

In this article, we present a robust scheme for detection of Devanagari or Bangla texts in scene images. These are the two most popular scripts in India. The proposed scheme is primarily based on two major characteristics of such texts - (i) variations in stroke thickness for text components of a script are low compared to their non-text counterparts and (ii) presence of a headline along with a few vertical downward strokes originating from this headline. We use the Euclidean distance transform to verify the general characteristics of texts in (i). Also, we apply the probabilistic Hough line transform to detect the characteristic headline of Devanagari and Bangla texts. Further, similarity and adjacency measures are applied to identify text regions, which do not satisfy the verification in (ii). The proposed approach has been simulated on a repository of 120 images taken from Indian roads and the results are encouraging. Also, we have discussed the applicability of the proposed scheme for detection of English texts. Towards this end, we have considered the training and test samples from the image database of ICDAR 2003 Robust Reading Competition. © 2012 Springer-Verlag Berlin Heidelberg.

关键词： Character recognition

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Continuous Motion Numeral recognition Using RNN Architecture in Air-Writing Environment 5th

Continuous Motion Numeral Recognition Using RNN Architecture...

引用

5th Asian Conference on pattern recognition, ACPR 2019

作者： Rahman, Adil Roy, Prasun Pal, Umapada Department of Information Technology Heritage Institute of Technology Kolkata India Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India

ISBN: (纸本)9783030414030

Air-writing, defined as character tracing in a three dimensional free space through hand gestures, is the way forward for peripheral-independent, virtual interaction with devices. While single unistroke character recognition is fairly simple, continuous writing recognition becomes challenging owing to absence of delimiters between characters. Moreover, stray hand motion while writing adds noise to the input, making accurate recognition difficult. The key to accurate recognition of air-written characters lies in noise elimination and character segmentation from continuous writing. We propose a robust and hardware-independent framework for multi-digit unistroke numeral recognition in air-writing environment. We present a sliding window based method which isolates a small segment of the spatio-temporal input from the air-writing activity for noise removal and digit segmentation. Recurrent Neural Networks (RNN) show great promise in dealing with temporal data and is the basis of our architecture. recognition of digits which have other digits as their sub-shapes is challenging. Capitalizing on how digits are commonly written, we propose a novel priority scheme to determine digit precedence. We only use sequential coordinates as input, which can be obtained from any generic camera, making our system widely accessible. Our experiments were conducted on English numerals using a combination of MNIST and Pendigits datasets along with our own air-written English numerals dataset (ISI-Air Dataset). Additionally, we have created a noise dataset to classify noise. We observe a drop in accuracy with increase in the number of digits written in a single continuous motion because of noise generated between digit transitions. However, under standard conditions, our system produced an accuracy of 98.45% and 82.89% for single and multiple digit English numerals, respectively. © Springer Nature Switzerland AG 2020.

关键词： Recurrent neural networks

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Fine classification of unconstrained handwritten Persian/Arabic numerals by removing confusion amongst similar classes

Fine classification of unconstrained handwritten Persian/Ara...

引用

ICDAR2009 - 10th International Conference on Document Analysis and recognition

作者： Alaei, Alireza Nagabhushan, P. Pal, Umapada Department of Studies in Computer Science University of Mysore Mysore 570 006 India Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata-108 India

ISBN: (纸本)9780769537252

In this paper, we propose two types of feature sets based on modified chain-code direction frequencies in the contour pixels of input image and modified transition features (horizontally and vertically). A multi-level support vector machine (SVM) is proposed as classifier to recognize Persian isolated digits. In first level, we combine similar shaped numerals into a single group and as result;we obtain 7 classes instead of 10 classes. We compute 196-dimension chain-code direction frequencies as features to discriminate 7 classes. In the second level, classes containing more than one numeral because of high resemblance in their shapes are considered. We use modified transition features (horizontally and vertically) for discriminating between two overlapping classes (0 and 1). To separate another overlapping group containing three numerals 2, 3 and 4 we first eliminate common parts of these digits (tail) and then compute chain code features. We employ SVM classifier for the classification and evaluate our scheme on 80,000 handwritten samples of Persian numerals [10]. Using 60,000 samples for training, we tested our scheme on other 20,000 samples and obtained 99.02% accuracy. © 2009 IEEE.

关键词： Support vector machines

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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 signature verification systems: A survey 11

Off-line signature verification systems: A survey

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Proceedings of the International Conference & Workshop on Emerging Trends in Technology

作者： Pal, S. Blumenstein, M. Pal, U. School of Information and Communication Technology Griffith University QLD Australia Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata-700108 India

ISBN: (纸本)9781450304498

Signatures are extensively used as a means of personal verification. Manual signature-based authentication of a large number of documents is a very difficult and time consuming task. Consequently for many years, in the field of protected communication and financial applications, we have observed an explosive growth in biometric personal authentication systems that are closely connected with measurable physical unique characteristics (hand geometry, iris scan, finger prints or DNA) or behavioural features. Human signatures provide secure means for confirmation and authorization in legal documents. So nowadays, automatic signature verification becomes an essential component. In order to convey the state-of-the-art in the field to researchers, in this paper we present a survey of off-line signature verification systems. Copyright © 2011 ACM.

关键词： Biometrics

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