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Detection and removal of graphical components in pre-printed documents

Publication Type : Journal Article

Publisher : International Journal of Applied Engineering Research

Source : International Journal of Applied Engineering Research, Volume 11, Issue 7, Pages 4849-4856, 1 May 2016.

Url : https://www.scopus.com/inward/record.uri?eid=2-s2.0-84966412972&partnerID=40&md5=1750212dbca80b74fcba972808da14b8

Keywords : mblem detection, Graphical components. Line detection, Moments and HOG features, Pre-printed documents

Campus : Mysuru

School : School of Arts and Sciences

Center : Computational Chemistry

Department : Computer Science

Year : 2016

Abstract : Pre-processing of document images is one of the most intensive operations for pre-printed document images. The recognition of text in pre-printed documents is most sensitive to graphical components coexisting with it. In this paper we address the problem of detection and removal of graphical components like logos, emblems and other symbolic entities, which leads to an error free document processing in the subsequent stages of Optical Character Recognition. The detection of graphical entities is performed by employing Zernike moments and histogram of gradient features, followed by which the line detection and removal is accomplished by masking the image with a vertical line structuring element by computation of region covered by convex hull within the area by structuring element in the image. The detection of line structuring element also addresses the problem of characters overlapping with lines leading to retention of the character during erosion of lines from the image. The experimental outcomes produced by emblem detection of algorithm are appreciable with accuracy of around 97% for the emblem detection and 92% accurate outcomes in case of line detection and removal. © Research India Publications.

Cite this Research Publication : Shobha Rani, N., Vineeth, P., Ajith, D., "Detection and removal of graphical components in pre-printed documents," International Journal of Applied Engineering Research, 11 (7), pp. 4849-4856, 2016

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