Segmentation of off-line cursive handwriting using linear programming

Abstract

Segmentation of cursive words into letters has been one of the major problems in handwriting recognition. We introduce a new segmentation algorithm, guided in part by the global characteristics of the handwriting. We find the successive segmentation points by evaluating a cost function at each point along the baseline. The cost of segmenting at a point is a weighted sum of four feature values at that point. The weights of the features are determined using linear programming. In our tests with 750 words written by 10 writers, 97% of the letter boundaries were correctly located. © 1998 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.