基于Radon变换的特征提取在步态识别中的应用

步态识别主要通过人体走路的姿势来识别人的身份．从经过背景减除后的人体运动图像序列中，根据面积变化确定运动周期，提取人体宽度信息，对下肢进行Radon变换，经处理后提取运动角度信息．对所得到的信息主分量分析变换后进行动态时间规整，采用最近邻分类器分类．该方法可以有效地降低人体运动时身体自遮挡及影子带来的影响．在小数据库上取得了很高的识别率．实验结果表明该方法有效．

Feature extraction based on Radon transform for gait recognition

Human gait recognition is the process of identifying individuals by their walking manners.The gait as one of biometrics has recently gained more and more interests from computer vision researchers.In this paper,the objects are got through subtracting backgrounds from the image sequences.A gait cycle is obtained through analyzing the changes of the objects' areas.The width features are extracted from human body.Radon transform is used to analyze the low limps and the limp angle features are got.After principal component analysis(PCA) transforming,dynamic time warping(DTW) is used to obtain the distances between the probe and the training sequences.The nearest-neighbor classifier is used to distinguish the classes.The experimental results demonstrate that the method is effective.