关键词: 笔画, 伪动态特征, 概率统计, 网格窗口, 文本相关度

Abstract: Concerning the problem that handwriting feature extraction in the past taking the whole character as the research object can not detect stable features under lower relevance of the text, this paper puts forward a method of handwriting spurious dynamic feature extraction based on strokes, getting rid of the bondage of the nexus of contracts dependence. The method introduces the thought of probability statistics, using grid window to detect the spurious dynamic feature of the strokes, such as the tendency and the width variation. The method uses weighted Euclidean distance, weighted chi-square distance and weighted Manhattan distance to calculate the similarity of the handwriting identification. In the database involving HIT-MW and HIT-SW, the method achieves the top-1 identification accuracy of 95.9% and the top-10 accuracy of 99.5% under higher relevance of the text, and the top-1 identification accuracy of 91.9% and the top-10 accuracy of 99.0% under lower relevance of the text. Experiments show that the method of handwriting spurious dynamic feature extraction based on strokes can obtain a good effect under lower relevance of the text.

Key words: strokes, spurious dynamic feature, probability statistics, grid window, text relevance