融合边缘检测与区域生长的交通图像分割方法

Traffic Image Segmentation Method Integrating Edge Detection and Region Growing

在交通监控中,如何从复杂的背景中分割运动物体是至关重要的一步,针对车辆的运动阴影对图像分割产生的不利影响,提出了一种新的融合边缘检测与区域生长的彩色图像分割算法,算法同时考虑了图像的彩色信息和空间信息。该算法首先对彩色图像边缘检测,并根据检测结果设置种子像素;再基于颜色相似性生长准则,结合边缘检测结果,对每个种子点进行区域生长;最后,利用区域合并算法对剩余的像素进行合并。实验结果表明该算法很大程度上克服了阴影给图像分割带来的不利影响。

Segmentation of moving object image with complex background is a crucial step in traffic surveillance. In order to solve the problem of the negative effects of moving object shade on a color image segmentation, a novel algorithm for color image segmentation integrated edge detection and region growing is proposed. Both the color information and spatial information of traffic color image are taken into account in this algorithm. Firstly, the edge of color image is detected by using a simple edge detection algorithm, and then, the seed pixels are selected in terms of the detection results of image. Secondly, seed pixel region growing is performed based on the hue similarity criterion and the results of edge detection. Finally, region merged algorithm is used to solve the remaining pixels that have not been classified into regions. Experimental results show that the negative effects of shading in a traffic color image on segmentation can be overcome to a great extent by using the proposed algorithm.