Multiple feature cooperation based handwritten Uighur character segmentation on mobile phone

Robust and accurate handwritten character segmentation is the essential step for automatic Uighur word recognition on mobile phone. However, it´s a hard work to do character segmentation due to Uighur´s cursive style and other characteristics. In this paper, a hybrid multiple feature cooperation based algorithm is presented, the main characteristics of the proposed approach include: (1) A multi-feature analysis method is given to extract connectivity, ownership, location and local peak characteristics, and all the features are cooperated to guide the segmentation; (2) A joint character segmentation model is presented to achieve the final segmentation results. In order to evaluate the performance of the proposed method, we have developed a handwritten Uighur character capture system on mobile phone, in addition, a labeling system is also designed to get the ground truth of character segmentation. Experimental results with difficult handwritten Uighur characteristics demonstrate the effectiveness of the algorithm.