基于图像处理的多视觉特征融合方法及其应用

Multi-Vision Feature Fusion Method Based on Image Processing with Its Application

针对目前轨面状态仍以人工经验判断、识别效率低等问题,提出一种基于图像处理的多视觉特征融合的轨面辨识方法。首先,对采集的不同状况轨面图像分割出铁轨接触面区域图像,并对接触面区域进行预处理去除噪声干扰;然后,计算接触面区域的灰度均值和方差来描述轨面图像颜色特征,采用灰度共生矩阵提取接触面区域纹理特征;再融合两种特征作为轨面状态判别依据,利用SVM对轨面状态进行识别。最后,通过实验仿真对所提方法进行验证与分析,结果证明了所提方法的有效性。

In view of the fact that the orbit state is still judged by artificial experience and low recognition efficiency,a track recognition method based on image processing and multi vision feature fusion is proposed.Firstly,the rail contact area image is segmented from the collected rail surface images under different conditions,and the noise interference is removed by preprocessing the contact area;then,the gray mean value and variance of the contact area are calculated to describe the color features of the rail surface image,with the gray level co-occurrence matrix used to extract the texture features of the contact area;then,the two features are fused as the basis for judging the rail surface state SVM is used to identify the state of rail surface.Finally,the simulation and validation of the proposed method are carried out,and the results verify the effectiveness of the proposed method.