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Touching text character localization in graphical documents using SIFT

Touching text character localization in graphical documents ...

引用

8th IAPR Workshop on Graphics recognition, GREC 2009

作者： Roy, Partha Pratim Pal, Umapada Lladós, Josep 08193 Spain Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata 108 India

ISBN: (纸本)364213727X

Interpretation of graphical document images is a challenging task as it requires proper understanding of text/graphics symbols present in such documents. Difficulties arise in graphical document recognition when text and symbol overlapped/touched. Intersection of text and symbols with graphical lines and curves occur frequently in graphical documents and hence separation of such symbols is very difficult. Several pattern recognition and classification techniques exist to recognize isolated text/symbol. But, the touching/overlapping text and symbol recognition has not yet been dealt successfully. An interesting technique, Scale Invariant Feature Transform (SIFT), originally devised for object recognition can take care of overlapping problems. Even if SIFT features have emerged as a very powerful object descriptors, their employment in graphical documents context has not been investigated much. In this paper we present the adaptation of the SIFT approach in the context of text character localization (spotting) in graphical documents. We evaluate the applicability of this technique in such documents and discuss the scope of improvement by combining some state-of-the-art approaches. © 2010 Springer-Verlag.

关键词： Character recognition

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A new wavelet-median-moment based method for multi-oriented video text detection 10

A new wavelet-median-moment based method for multi-oriented ...

引用

2010 IAPR Workshop on Document Analysis Systems, DAS 2010

作者： Shivakumara, Palaiahnakote Dutta, Anjan Tan, Chew Lim Pal, Umapada Department of Computer Science School of Computing National University of Singapore Singapore Singapore Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India

ISBN: (纸本)9781605587738

In this paper, we present a new method based on wavelet-median-moments and a novel idea of angle projection for detecting multi-oriented text in video. The proposed method uses wavelet decomposition first to obtain three high frequency sub-bands (LH, HL and HH) and then median moments are computed on the average sub-bands of the three high frequency sub-bands to brighten the text pixels. K-means clustering (K=2) is used for obtaining text pixels from the wavelet-median-moments features (WMMF). Text candidates are obtained by mapping the output of K-means on Sobel edge map of the original input frame. To deal with multi-oriented text, we introduce a new idea of Angle Projection (AP) based on boundary growing and nearest neighbor concepts from the text candidates instead of conventional projection profiles. The proposed method is experimented on horizontal text data, non-horizontal text data, temporal data, non-text data and camera based images (scene text data of ICDAR 2003 competition) to show that the proposed method is superior to existing methods. © Copyright 2010 ACM.

关键词： Pixels

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A baseline dependent approach for Persian handwritten character segmentation

A baseline dependent approach for Persian handwritten charac...

引用

International Conference on pattern recognition

作者： Alaei, Alireza Nagabhushan, P. Pal, Umapada Department of Studies in Computer Science University of Mysore Mysore 570006 India Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata-108 India

ISBN: (纸本)9780769541099

In this paper, an efficient approach to segment Persian off-line handwritten text-line into characters is presented. The proposed algorithm first traces the baseline of the input text-line image and straightens it. Subsequently, it over-segments each word/subwords using features extracted from histogram analysis and then removes extra segmentation points using some baseline dependent as well as language dependent rules. We tested the proposed character segmentation scheme with 2 different datasets. On a test set of 899 Persian words/subwords created by us, 90.26% of the characters were segmented correctly. From another dataset of 200 handwritten Arabic word images [11] we obtained 93.49% correct segmentation accuracy. © 2010 IEEE.

关键词： Image segmentation

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A new two-stage scheme for the recognition of persian handwritten characters

A new two-stage scheme for the recognition of persian handwr...

引用

International Conference on Frontiers in Handwriting recognition

ISBN: (纸本)9780769542218

In this paper, a two-stage scheme for the recognition of Persian handwritten isolated characters is proposed. In the first stage, similar shaped characters are categorized into groups and as a result, 8 groups are obtained from 32 Persian basic characters. In the second stage, the groups containing more than one similar shape characters are considered further for the final recognition. Feature extraction is based on undersampled bitmaps technique and modified chain-code direction frequencies. For the first stage features, we compute 49-dimension features based on undersampled bitmaps from 49 non-overlapping 7x7 window-maps. 196-dimension chain-code direction frequencies from 49 overlapping 9x9 window-maps are computed and used as features for the second stage of the proposed scheme. Classifiers are one-against-other support vector machines (SVM). We evaluated our scheme on a standard dataset of Persian handwritten characters. Using 36682 samples for training, we tested our scheme on other 15338 samples and obtained 98.10% and 96.68% correct recognition rates when considered 8-class and 32-class problems, respectively. © 2010 IEEE.

关键词： Support vector machines

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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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A new method for handwritten scene text detection in video

A new method for handwritten scene text detection in video

引用

International Conference on Frontiers in Handwriting recognition

作者： Shivakumara, Palaiahnakote Dutta, Anjan Pal, Umapada Tan, Chew Lim School of Computing National University of Singapore Singapore Singapore Computer Vision Center Universitat Autònoma de Barcelona Barcelona Spain Computer Vision and Pattern Recognition Unit Indian Statistical Institute India

ISBN: (纸本)9780769542218

There are many video images where hand written text may appear. Therefore handwritten scene text detection in video is essential and useful for many applications for efficient indexing, retrieval etc. Also there are many video frames where text line may be multi-oriented in nature. To the best of our knowledge there is no work on handwritten text detection in video, which is multi-oriented in nature. In this paper, we present a new method based on maximum color difference and boundary growing method for detection of multi-oriented handwritten scene text in video. The method computes maximum color difference for the average of R, G and B channels of the original frame to enhance the text information. The output of maximum color difference is fed to a K-means algorithm with K=2 to separate text and non-text clusters. Text candidates are obtained by intersecting the text cluster with the Sobel output of the original frame. To tackle the fundamental problem of different orientations and skews of handwritten text, boundary growing method based on a nearest neighbor concept is employed. We evaluate the proposed method by testing on our own handwritten text database and publicly available video data (Hua's data). Experimental results obtained from the proposed method are promising. © 2010 IEEE.

关键词： Color

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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

2010 19th International Conference on computer Communications and Networks, ICCCN 2010

作者： Chattopadhyay, T. Pal, Arpan Garain, Utpal Innovation Lab. Kolkata Tata Consultancy Services Kolkata India Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India

ISBN: (纸本)9781424471164

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. © 2010 IEEE.

关键词： Optical character recognition

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Shape code based word-image matching for retrieval of Indian multi-lingual documents

Shape code based word-image matching for retrieval of Indian...

引用

International Conference on pattern recognition

作者： Tarafdar, Arundhati Mondal, Ranju Pal, Srikanta Pal, Umapada Kimura, Fumitaka Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata-700108 India Graduate School of Engineering Mie University Kurimamachiya-cho Tsu Japan

ISBN: (纸本)9780769541099

In the current scenario retrieving information from document images is a challenging problem. In this paper we propose a shape code based word-image matching (words-potting) technique for retrieval of multilingual documents written in Indian languages. Here, each query word image to be searched is represented by a primitive shape code using (i) zonal information of extreme points (ii) vertical shape based feature (iii) crossing count (with respect to vertical bar position) (iv) loop shape and position (v) background information etc. Each candidate word (a word having similar aspect ratio and topological feature to the query word) of the document is also coded accordingly. Then, an inexact string matching technique is used to measure the similarity between the primitive codes generated from the query word image and each candidate word of the document with which the query image is to be searched. Based on the similarity score, we retrieve the document where the query image is found. Experimental results on Bangla, Devnagari and Gurumukhi scripts document image databases confirm the feasibility and efficiency of our proposed approach. © 2010 IEEE.

关键词： Image matching

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Text independent writer identification for Bengali script

Text independent writer identification for Bengali script

引用

International Conference on pattern recognition

作者： Chanda, Sukalpa Franke, Katrin Pal, Umapada Wakabayashi, Tetsushi Department of Computer Science and Media Technology Gjøvik University College Norway Computer Vision and Pattern Recognition Unit Indian Statistical Institute India Graduate School of Engineering Mie University Japan

ISBN: (纸本)9780769541099

Automatic identification of an individual based on his/her handwriting characteristics is an important forensic tool. In a computational forensic scenario, presence of huge amount of text/information in a questioned document cannot be always ensured. Also, compromising in terms of systems reliability under such situation is not desirable. We here propose a system to encounter such adverse situation in the context of Bengali script. Experiments with discrete directional feature and gradient feature are reported here, along with Support Vector Machine (SVM) as classifier. We got promising results of 95.19% writer identification accuracy at first top choice and 99.03% when considering first three top choices. © 2010 IEEE.

关键词： Support vector machines

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Script identification - A Han & Roman script perspective

Script identification - A Han & Roman script perspective

引用

2010 20th International Conference on pattern recognition, ICPR 2010

作者： Chanda, Sukalpa Pal, Umapada Franke, Katrin Kimura, Fumitaka Department of Computer Science and Media Tech. Gjøvik University College Norway Computer Vision and Pattern Recognition Unit Indian Statistical Institute India Graduate School of Engineering Mie University Japan

ISBN: (纸本)9780769541099

All Han-based scripts (Chinese, Japanese, and Korean) possess similar visual characteristics. Hence system development for identification of Chinese, Japanese and Korean scripts from a single document page is quite challenging. It is noted that a Han-based document page might also have Roman script in them. A multi-script OCR system dealing with Chinese, Japanese, Korean, and Roman scripts, demands identification of scripts before execution of respective OCR modules. We propose a system to address this problem using directional features along with a Gaussian Kernel-based Support Vector Machine. We got promising results of 98.39% script identification accuracy at character level and 99.85% at block level, when no rejection was considered. © 2010 IEEE.

关键词： Optical character recognition

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