Telugu Word Segmentation Using Fringe Maps

Abstract

In this paper, we propose a word segmentation method that is based on fringe maps on Telugu script. Our objective is to create a data set of word images for enabling direct training for recognition on those. The standard methods employed for the task of word segmentation in Telugu OCR systems are projection profiles and run-length smearing. However those methods have their limitations. In this work a different application of fringe maps is shown for line segmentation into words. Fringes were previously applied successfully for carrying out classification and line segmentation. Telugu script, which has consonant modifiers that are usually placed below or below-right to the base consonants. This kind of orthographic property leads to characters that may touch each other. One way to deal with touched characters is to make use of segmentation free methods, which do not need prior segmentation of word images into characters or connected components. The novelty of our method is that we analyze fringe maps of document images to find an appropriate fringe value threshold and apply it for word segmentation of Telugu documents. Encouraging results are observed with our fringe value threshold based word segmentation. We observe that choosing higher threshold fringe values leads to under-segmentation of words, whereas lower values cause over-segmentation of words. Our word segmentation approach is successfully compared with the widely used projection profiles based word segmentation method.