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Automatic character recognition in complex images

Publication Type : Conference Paper

Publisher : Procedia Engineering

Source : Procedia Engineering, Volume 30, Coimbatore, p.218-225 (2012)

Url : http://www.scopus.com/inward/record.url?eid=2-s2.0-84859078508&partnerID=40&md5=d68361eae18afecd1d6ab6c446eabe7b

Keywords : Assignment of, Banking sectors, Character recognition, Character recognition system, Communication, Comparative studies, Complex image, Eigenfeatures, Image processing, Market surveys, Object identification, Potential applications, Printed documents, Probabilistic, Recognition rates, Surface deformation, Surveys, Systems analysis, Text data, Text extraction, Textual representation, Wavelet features

Campus : Coimbatore

School : School of Engineering

Center : Computational Engineering and Networking

Department : Computer Science and Engineering

Year : 2012

Abstract : pCharacter recognition system has received considerable attention in recent years due to the tremendous need for digitization of printed documents. The textual representations of images convey information relating to what is actually depicted in the image as well as what the image is about. Manual assignment of text data from images is time consuming and costly. Hence automation of text extraction from images is a challenging area in image processing due to its potential applications. Since text contained in images might be of different fonts, different languages, having surface deformation, poor quality, or even blurred, the proper text extraction becomes very difficult. If all these difficulties are overcome, the text extraction can be beneficial for different applications. Some of these applications include character recognitions in surveillance, object identification, banking sector, market survey and all. The recognition rate drops drastically in some methods, when the font style or size of the character changes. This survey addresses a comparative study of different techniques available for extraction of characters from complex images./p

Cite this Research Publication : A. Ka Sadasivan and Senthilkumar, Tb, “Automatic character recognition in complex images”, in Procedia Engineering, Coimbatore, 2012, vol. 30, pp. 218-225.

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