Linear Curve Fitting-Based Headline Estimation in Handwritten Words for Indian Scripts

Abstract

Most segmentation algorithms for Indian scripts require some prior knowledge about the structure of a handwritten word to efficiently fragment the word into constituent characters. Zone detection is a considerably used strategy for this purpose. Headline estimation is a salient part of zone detection. In the present work, we propose a method that uses simple linear regression for estimating headlines present in handwritten words. This method efficiently detects headline in three Indian scripts, namely Bangla, Devanagari, and Gurmukhi. The proposed method is able to detect headlines in skewed word images and provides accurate result even when the headline is discontinuous or mostly absent. We have compared our method with a recent work to show the efficacy of our proposed methodology.