基于边缘特征的工件图像匹配

Image Match for Workpiece Based on Edge Characteristics

为了解决亮度不均匀等复杂环境下的图像匹配问题,改进了一种基于边缘匹配的工件识别算法。该算法对原始图像和模板图像采用样条小波进行增强,用Canny算子提取的边缘信息作为匹配特征,将改进的Hausdorff距离作为图像匹配的相似性度量,在搜索过程中采用了基于种群代沟信息的自适应遗传算法,在不损失解的质量的情况下,使遗传算法求解效率得到明显的改善。实验结果表明,该算法不仅加快了匹配过程,对于光照条件的变化具有很好的适应能力,而且能有效解决不易提取边缘信息等情况下的图像匹配识别问题。

To solve the problem of image matching under complex conditions including background and uneven illumination, a workpiece recognition algorithm based on edge matching approach is improved. The algorithm enhances primitive image and template image by spline wavelet, adopts the edge information captured by Canny operator as a matching feature, applies improved Hausdorff distance to measure the degree of similarity between two objects and performs the search by adaptive genetic algorithm based on population generation gap information. The efficiency of the genetic algorithm is improved obviously without loss of quality. Experimental results show that the proposed algorithm not only speeds up the matching process greatly and is robust to the illumination variation but also effectively solves the problem of image matching and recognition when the edge information is not easy to be extracted.