The handwritten numeral recognition is a technology, which auto recognizes the handwriting Arabian numeral via machines or computers, and a special field in the Optical Character Recognition technology. Then handwritten numeral recognition research is greatly general-purpose and significative, because of the universal Arabic numerals. On the same score, the handwritten numeral, recognition technologies are playing an important role in a number of automatization systems.In this paper, the main study focused on image pre-processing and selection of appropriate feature vectors, and to realize a complete system of handwritten numeral recognition. There are several common comparisons of binarization algorithm in this article, and choose the gradient-based binarization algorithm finally; and objecting to the defection of traditional methods of structural point detection, a solution to the problem was put up in this article. In addition, this paper also raises the convex-concave feature as one of the character feature vectors.Through the NIST test data, experimental data shows that the digital identification system designed for handwritten numeral recognition has a high recognition rate. |