多重图像轮廓特征结合的步态识别算法

为提高图像步态识别率，研究了一种基于图像轮廓多特征的步态识别算法.该算法首先从图像轮廓的基础上选取了图像步态的3个特征；然后，通过建立不变矩、帧差百分比的动态特征，并结合改进的角度距离的静态特征，实现了图像轮廓特征的提取；最后，通过对传统的K近邻法改进，完成了图像步态识别.实验结果表明：单用静态特征的步态识别率最高为91.94%；结合动态特征，并在改进分类器下获得最高为99.19%的识别率.
This paper proposes a gait recognition algorithm based on three kinds of features from the image's silhouette. It extracts silhouette features by establishing dynamic information of invariant moment and percentage of frame difference, combining the modified angle distance of static information. It realizes the gait recognition via a modified K neighbor method. The experimental result shows that the recognition ratio achieves 91.94% with the static featureis only, and reaches 99.19% with the dynamic features under the improved classifier.