Features of off-line handwritten digit recognition based on principal curves

Firstly soft k-segments algorithm of principal curves are used to extract the structural features of training data; Secondly the classification features used for characters coarse classification and precise classification are chosen by analyzing the structural features of principal curves in detail; Finally coarse classification and precise classification are separately carried out in off-line handwritten digits recognition. The result of the experiment shows that these features have good discriminating power of similar characters and the algorithm can effectively improve the recognition rate of off-line handwritten digits. The proposed method provides a new approach to the research for off-line handwritten digits recognition.