一种改进的OSID的图像匹配算法

An improved image matching algorithm based on OSID

针对OSID在构建描述符时未考虑一个特征点的图像块里存在其他特征点,以及生成直方图描述子匹配速度较慢的问题,提出一种基于OSID的改进二进制描述符。在OSID描述符构建的过程中,扇形个数m的选择是固定的,因此提出当一个特征点的图像块里有多个特征点时,尝试将m的值自适应,丰富描述子所包含的信息,提高算法的正确匹配率;并将OSID最后生成的直方图描述子编码成二进制描述子,使用汉明距离代替欧氏距离进行图像匹配,提高算法的匹配速度。在标准数据集上进行测试,结果表明在复杂的视点变化、图像模糊和JPEG压缩等场景下,改进OSID的匹配精度优于同类描述符以及原算法。

In order to solve the problem that there are other feature points in the image block without considering one feature point in OSID,and the matching speed of histogram descriptor is slow,an improved binary descriptor based on OSID is proposed.In the process of constructing OSID descriptors,the selection of M is fixed.Therefore,when there are multiple feature points in an image block of a feature point,we propose to try to adapt the value of M,enrich the information contained in the descriptors,and improve the correct matching rate of the algorithm.Meanwhile,the histogram descriptors finally generated by OSID are encoded into binary descriptors,and Hamming distance replaces European distance for image matching,so as to improve the matching speed of the algorithm.The test results on the standard dataset show that the improved OSID has better matching accuracy than the similar descriptors and the original algorithm in complex view changes,image blur and JPEG compression scenarios.