A method for segmentation of cursive handwritings and its application to character shape extraction

Image processing and shape analysis are important and useful in many document processing applications, such as segmentation of connected characters, recognition of confusing character shapes, etc. A skeleton segmentation algorithm and a shape analysis method based on the segmentation result is presented. The motivation of the work presented in this paper is the idea that the basic elements in character shapes are line segments with uniform directional attributes. We define these line segments as image cells. An algorithm is carefully designed to segment the character skeletons into image cells robustly. Based on the image cells, a new selective attention approach for character shape extraction is proposed. To guarantee the robustness of the proposed algorithm, the shape extraction problem is decomposed into two steps: attention focus area detection and shape growing. The effectiveness of the proposed algorithms is verified by experimental results.