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A Survey on Text Segmentation Methods for Digital Images


Vikas V Sonwane , K. K. Wagh Institute of Education Engineering & Research ; Prof. N.M.Shahane, K. K. Wagh Institute of Education Engineering & Research


Born-digital compound image, Text segmentation, Image activity measure


Images are important information carriers which are often used in email messages and web pages to attach textual information. In Born digital compound image (BDCI) text and graphics/pictures come together on digital devices having certain distinct characteristics like low resolution (easy for online transmission and to display on screen) and text is created digitally on image. Text from BDCI can be effectively adopted for large number of applications likes to retrieve contents of web, to improve indexing, to enhance content accessibility and content filtering. There are several problems to distinguish texts from BDCI because, text appears in various styles (i.e. Orientation, size, and color), some neighbor texts are connected, and some text characters are superimposed on pictorial region which may lead to misclassification. Although researchers have proposed many methods in which character-level and block-based objects are commonly assumed to separate text from compound images. But these methods failed to extract reliable features to detect all texts as well as to identify connected components. Some recent methods based on distribution of pixel variations and image activity measures can able to precisely segment textual regions from BDCI.

Other Details

Paper ID: IJSRDV3I120309
Published in: Volume : 3, Issue : 12
Publication Date: 01/03/2016
Page(s): 427-429

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