基于改进标记分水岭的彩色踏面图像分割

The Color Tread Image Segmentation Based on Improved Labeled Watershed

踏面图像分割是实现踏面区域与背景分离的过程,是联系图像预处理与踏面图像缺陷检测的纽带。针对传统踏面图像分割方法处理过程中存在的图像信息缺失、区域轮廓分割精度低和抗干扰能力差的问题,提出了一种基于改进分水岭算法的彩色踏面图像分割方法。首先使用带色彩恢复的多尺度视网膜增强(MSRCR)调整踏面图像入射分量与反射分量及RGB 3个颜色通道之间的比例;然后直接计算彩色图像梯度图,通过改进RGB彩色分量融合运算完成彩色梯度图像前景与背景的标记后进行分水岭变换得到初始分割结果;最后结合踏面轮廓方位特点设计图像连通域提取分割算法完成踏面曲面提取。实验结果表明,本方法分割图像边缘特性好,颜色保真,抗雾霾、光照干扰能力强,可以获得理想的车轮踏面分割结果。

The tread image segmentation is the process of realizing the separation of tread area and background, which is the link between image preprocessing and tread image defect detection. Aimed at the problem of missing image information, low precision of regional contour segmentation and poor anti-interference ability, a method of color tread image segmentation based on improving watershed algorithm is presented in this paper. Firstly, the proportion of the incident component of the tread image with the reflective component and the RGB three color channel is adjusted by using the multi-scale retinal enhancement （MSRCR） with color restoration. Then the color image gradient graph is calculated directly. The color gradient image foreground and background mark is completed by improving RGB color component fusion operation and then the initial segmentation result is obtained by the watershed transformation. Finally, combined with the tread contour azimuth characteristic, image connected domain extraction segmentation algorithm is designed and the tread surface extraction is completed. The experimental results show that the method is good to divide the edges of the image, the color fidelity, the fog haze, the illumination disturbance ability, and obtain the ideal wheel tread segmentation results.