摘要
在路况监测中,常常需要得到路况图像的边缘轮廓线,以便诊断路面的病害情况。为适应这种需求,提出了基于模糊和遗传算法的路况图像边缘检测算法。针对用模糊算法构造相应隶属函数进行图像边缘检测中存在的低灰度图像信息丢失、边缘检测速度较慢等问题,利用遗传和模糊算法的优点构造边缘检测算法。这种方法使得模糊处理后丢失的低灰度信息得以恢复,提高了算法的效率,增强了算法的适应性。算法检测出的图像边缘与传统模糊算法提取的图像边缘相比较,结果更加清晰完整。
So the edge detection method of road surface picture based on fuzzy and genetic algorithm is proposed in this paper in order to meet this demand.The advantage of genetic and fuzzy algorithm is used to construct edge measure algorithms in order to solve some problems such as the low gray signal is lost,the speed measured on the edge is relatively low and so on when you measure the edge of image using the jurisdiction of function and correspondingly with the structure of the one degree of function.It can transform the picture in to matrix which is under the jurisdiction of degrees quickly and transform against matrix which is under the jurisdiction of degrees in to picture quickly.The low gray information is got after fuzzy processing.So it has improved the efficiency of the algorithm,and has strengthened the adaptability of the algorithm.
出处
《工业控制计算机》
2012年第4期80-82,共3页
Industrial Control Computer
关键词
边缘检测
模糊
阈值分割
隶属度函数
路面裂缝
edge-detection
fuzzy
threshold value segmentation
membership function
pavement crack