A new methodology for gray-scale character segmentation and recognition

Abstract

Generally speaking, through the binarization of gray-scale images, useful information for the segmentation of touching or overlapping characters may be lost. If we analyze gray-scale images, however, specific topographic features and the variation of intensity can be observed in the character boundaries. We believe that such kinds of clues obtained from gray-scale images should be useful for efficient character segmentation. In this paper, we propose a new methodology for character segmentation and recognition which makes the best use of the characteristics of gray-scale images. In the proposed methodology, the character segmentation regions are determined by using projection profiles and topographic features extracted form gray-scale images. Then the nonlinear character segmentation path in each character segmentation region is found by using multistage graph search algorithm. Finally, in order to confirm the character segmentation paths and recognition results, recognition based segmentation method is adopted.