Enhanced Character Segmentation for Format-Free Japanese Text Recognition
Kha Cong Nguyen, Nakagawa Masaki · 2016
This paper presents Optical Handwritten Text Recognition (OHTR) for casually handwritten Japanese text. Distortions due to handwriting and the mixture of complex Chinese characters with simple phonetic and alphanumeric characters leave OHTR for handwritten Japanese text as still one of the hardest problems. This paper proposes a method for segmenting characters in handwritten text-pages, and a robust recognition model for over-segmentation. Stroke Width Transform (SWT), a new method of bridge separation at fork points and Voronoi diagrams with two improvements are proposed for character segmentation, and then a recognition model is employed with linguistic context and geometric context to recognize segmented characters. The results of experiments show that the proposed method improves the segmentation and recognition rates and each component in the method contributes to the improvement.