Accuracy improvement for handwritten Japanese word recognition by combination of character and word recognizer

Abstract

This paper proposes a combination method of character recognizer (CR) and word recognizer (WR) for Japanese handwritten words. CR is composed of character segmentation, isolated character recognition, and postprocessing. On the other hand, WR recognizes word images holistically based on a given word lexicon. These methods have been used as key modules in handwritten address recognition but have not been compared quantitatively up to now. In this paper, CR and WR are first empirically compared with each other using synthesized words generated from character images. Based on the comparison, a combination method is then proposed Experimental results show that the combination approach can achieve better recognition performance than the other two methods.