An Effective Character Separation Method for Online Cursive Uyghur Handwriting

There are many connected characters in cursive Uyghur handwriting, which makes the segmentation and recognition of Uyghur words very difficult. To enable large vocabulary Uyghur word recognition using character models, we propose a character separation method for over-segmentation in online cursive Uyghur handwriting. After removing delayed strokes from the handwritten words, potential breakpoints are detected from concavities and ligatures by temporal and shape analysis of the stroke trajectory. Our preliminary experiments on an online Uyghur word dataset demonstrate that the proposed method can give a high recall rate of segmentation point detection.