列车车轮踏面缺陷的图像区域提取

Defect region extraction in images of train wheel tread

建立了基于机器视觉的踏面缺陷检测系统,研究了该系统的踏面缺陷图像区域提取技术。采用基于平稳小波自适应阈值算法提取踏面区域;然后,根据踏面剥离缺陷图像特征,利用基于分块思想的粗定位和精定位组合的方法提取剥离图像区域;最后,根据踏面擦伤缺陷图像特征,利用基于踏面边缘线扫描搜索擦伤区域的方法提取擦伤图像区域。用两个实例验证了提出方法的有效性,实验结果表明:系统对剥离和擦伤两种缺陷的漏识率分别为8.3%和5.3%,误识率为5.1%,从而为后续特征提取和缺陷识别奠定了基础。

In order to realize defect inspection for train wheel treads, a defect inspecting system of the train wheel treads based on computer vision is established and defect region extraction techniques for the images of the train wheel treads are investigated. The tread region is extracted by an adaptive thresholds algorithm, then, a method combining the approximate location based on the block segmentation with the accurate location is adopted to extract the burning defect regions,and the peeling defect extraction method based on searching tread edge lines is used to extract the peeling defect regions. Two experimental examples are carried out to verify the effectiveness of the proposed method. The experimental results indicate that the missing recognition rates of the burnings and peelings are 8.3 and 5.3%, respectively, and false acceptance rate is 5.1%,which shows that proposed method can lay the basis for the feature extraction and defect recognition further.