检索结果-内蒙古大学图书馆

作者： Wachenfeld, Steffen Terlunen, Sebastian Jiang, Xiaoyi Department of Computer Science Computer Vision and Pattern Recognition Group University of Munster Germany

ISBN: (纸本)9781424421756

In this paper we present an algorithm for the recognition of 1D barcodes using camera phones, which is highly robust regarding the the typical image distortions. We have created a database of barcode images, which covers typical distortions, such as inhomogeneous illumination, reflections, or blurriness due to camera movement. We present results from experiments with over 1,000 images from this database using a Matlab implementation of our algorithm, as well as experiments on the go, where a Symbian C++ implementation running on a camera phone is used to recognize barcodes in daily life situations. The proposed algorithm shows a close to 100% accuracy in real life situations and yields a very good resolution dependent performance on our database, ranging from 90.5% (640 × 480) up to 99.2% (2592 × 1944). The database is freely available for other researchers. © 2008 IEEE.

关键词： Database systems

来源：评论

学校读者我要写书评

暂无评论

Extraction of type style-based meta-information from imaged documents

引用

International Journal on Document Analysis and recognition 2001年第3期3卷 138-149页

作者： Chaudhuri, B.B. Garain, U. Computer Vision and Pattern Recognition Unit Indian Statistical Institute 203 B.T. Road Calcutta 700 035 India

Extraction of some meta-information from printed documents without carrying out optical character recognition (OCR) is considered. It can be statistically verified that important terms in technical articles are mainly printed in italic, bold, and all-capital style. A quick approach to detecting them is proposed here. This approach is based on the global shape heuristics of these styles of any font. Important words in a document are sometimes printed in larger size as well. A smart approach for the determination of font size is also presented. Detection of type styles helps in improving OCR performance, especially for reading italicized text. Another advantage to identifying word type styles and font size has been discussed in the context of extracting: (i) different logical labels;and (ii) important terms from the document. Experimental results on the performance of the approach on a large number of good quality, as well as degraded, document images are presented. © 2001 Springer-Verlag Berlin Heidelberg.

关键词： Optical character recognition

来源：评论

学校读者我要写书评

暂无评论

A comparative study between ISITRA and wavelet filters

A comparative study between ISITRA and wavelet filters

引用

IEEE INDICON 2004 - 1st India Annual Conference

作者： Singh, Yumnam Kirani Parui, Swapan Kumar Banerjee, Shuvransu Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata-700108

ISBN: (纸本)0780389093

ISITRA is a new scheme of signal decomposition and reconstruction. In ISITRA, the space of PRF sets is much larger and more well-behaved than that in the existing schemes like filter bank or wavelets. Since such a space is constrained, it is mapped to an unconstrained space in which an optimization technique can be applied to find optimal PRF sets in terms of some criterion. Our criterion here is based on Mean Square Error and the optimization technique used is genetic algorithms. Optimal PRF sets thus found perform better than the popular Daubechies' filters for a compression task. © 2004 IEEE.

关键词： Optical filters

来源：评论

学校读者我要写书评

暂无评论

Issues in searching for indian language web content

Issues in searching for indian language web content

引用

2nd ACM Workshop on Improving Non English Web Searching, iNEWS'08, Co-located with the 17th ACM Conference on Information and Knowledge Management, CIKM 2008

作者： Pal, Dipasree Majumder, Prasenjit Mitra, Mandar Mitra, Sukanya Sen, Aparajita Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India

ISBN: (纸本)9781605584164

This paper looks at the problem of searching for Indian language (IL) content on the Web. Even though the amount of IL content that is available on the Web is growing rapidly, searching through this content using the most popular websearch engines poses certain problems. Since the popular search engines do not use any stemming / orthographic normalization for Indian languages, recall levels for IL searches can be low. We provide some examples to indicate the extent of this problem, and suggest a simple and efficient solution to the problem. Copyright 2008 ACM.

关键词： Search engines

来源：评论

学校读者我要写书评

暂无评论

A simple real-word error detection and correction using local word bigram and trigram 25

A simple real-word error detection and correction using loca...

引用

25th Conference on Computational Linguistics and Speech Processing, ROCLING 2013

作者： Samanta, Pratip Chaudhuri, Bidyut B. Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India

ISBN: (纸本)9789573079262

Spelling error is broadly classified in two categories namely non word error and real word error. In this paper a localized real word error detection and correction method is proposed where the scores of bigrams generated by immediate left and right neighbour of the candidate word and the trigram of these three words are combined. A single character position error model is assumed so that if a word W is erroneous then the correct word belongs to the set of real words S generated by single character edit operation on W. The above combined score is calculated also on all members of S. These words are ranked in the decreasing order of the score. By observing the rank and using a rule based approach, the error decision and correction candidates are simultaneously selected. The approach gives comparable accuracy with other existing approaches but is computationally attractive. Since only left and right neighbor are involved, multiple errors in a sentence can also be detected (if the error occurs in every alternate words). © ROCLING *** rights reserved.

关键词： Error detection

来源：评论

学校读者我要写书评

暂无评论

An end-to-end system for bangla online handwriting recognition 15

An end-to-end system for bangla online handwriting recogniti...

引用

15th International Conference on Frontiers in Handwriting recognition, ICFHR 2016

作者： Bhattacharya, Soumik Maitra, Durjoy Sen Bhattacharya, Ujjwal Parui, Swapan K. Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India

ISBN: (纸本)9781509009817

A few studies of online Bangla handwriting recognition such as isolated character recognition or limited vocabulary cursive word recognition are found in the literature. However, development of an end-to-end recognition system of unconstrained online Bangla handwritten texts has not been duly attempted so far. In the present report, we describe a similar system which takes a piece of continuous online handwritten Bangla texts as the input. It first segments the input texts into individual lines, each line into its constituent words and each word into sub-strokes. In the present study, 152 different symbols which include basic characters, character modifiers, frequently used conjunct characters, a few special characters and numerals have been considered. The entire set of sub-strokes obtained from the training sample set has been exhaustively studied by 3 experts and 76 different shapes of sub-strokes have been identified based on consensus among these experts. Also, it has been observed that a character may produce at most 3 sub-strokes. Since a piece of Bangla texts often contains either Bangla or English numerals, the present character set consists of both the numeral set and 3 numeral shapes are common to both the scripts. The proposed recognition system uses two classifiers, one for characters and the other for sub-strokes. Sub-strokes are fed to the character classifier in their temporal order. A single sub-stroke followed by two consecutive sub-strokes and finally three successive sub-strokes are passed to the character classifier and the first two top responses of the character classifier among the three cases are compared. If the difference is less than a threshold, the response of sub-stroke classifier is used to reach a final decision. The proposed system provided 94.3% character level accuracy on a test set consisting of 33,453 word samples written by 31 writers. © 2016 IEEE.

关键词： Character recognition

来源：评论

学校读者我要写书评

暂无评论

Indian language multimedia and information retrieval 3

Indian language multimedia and information retrieval

引用

3rd International Conference on Computational Intelligence and Multimedia Applications, ICCIMA 1999

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

ISBN: (纸本)0769503004

Over the last decade or so, remarkable developments in computer technology have given a major impetus to research in the field of multimedia. With the proliferation of the Internet and the increasingly widespread use of sophisticated computers, the multimedia revolution has arrived in India as well. It is therefore time to take stock of the situation: to evaluate how existing techniques can be used in the Indian context and to determine what new methods have to be developed. This paper summarizes the current state of multimedia technology in India and points to directions for further work. As more and more people in India begin to use computers and the Internet, multimedia capabilities will start playing a vital role in solving problems in many different areas. Education is probably one of the most important areas where multimedia technology can have a major impact. Already, multimedia educational systems are being developed in Indian languages. Several interactive encyclopaedia-like environments are also being marketed on CD-ROMs, and cover topics ranging from Indian classical music to Indian history, using text, images and sound. Some of the other possible applications of multimedia technology are: the development of digital libraries, news and information dissemination services, medicine, business and commerce, and the entertainment industry. Multimedia information technology is thus poised to become an exciting area for research and development activities in India. © 1999 IEEE.

关键词： CD-ROM

来源：评论

学校读者我要写书评

暂无评论

Processing of struck-out handwriting

Processing of struck-out handwriting

引用

2nd Indian International Conference on Artificial Intelligence, IICAI 2005

作者： Bhattacharya, U. Chaudhuri, B.B. Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India

ISBN: (纸本)0972741216

Struck-out words are often found in handwritten manuscripts. A realistic off-line handwriting recognition system should take care of this common aspect. A simple but efficient approach to this problem is to subject each handwritten word to a two-class classifier in the initial stage. This classifier should take decision to pass the word to a word recognition engine in the next step or discard it as a struck-out/wrong word. In the present work, we studied a stroke analysis based technique, which can classify an input word as a correct or wrong (struck-out) word. We simulated the proposed approach on a database of 466 words collected from handwritten manuscripts of different languages and the results are promising. Copyright © IICAI 2005.

关键词： Artificial intelligence

来源：评论

学校读者我要写书评

暂无评论

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

Offline handwritten Devanagari word recognition: Information...

引用

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)

来源：评论

学校读者我要写书评

暂无评论

OCR error detection and correction of an inflectional Indian language script

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

引用

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

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：