基于SURF算法的微观驱替图像配准

Microscopic displacement image registration based on SURF algorithm

针对快速鲁棒特征(SURF)算法对微观驱替图像进行配准存在的误匹配比例较高和由于提取的特征点过多导致时间偏长的问题,提出了一种改进的SURF算法。利用了微观驱替模型的特点,提取出信息量相对比较丰富的边界,仅在边界和边界附近提取特征点。借鉴了Hassion角点检测的方法,筛选出那些满足设定条件的稳定的特征点。实验证明,本文提出的方法在匹配正确率上得到了提高。同时,特征点匹配的耗时有所减少。

This paper proposes a registration method for microscopic displacement image based on Speeded Up Robust Features（SURF） algorithm. This method is designed to solve problems of high mismatch ratio in microscopic displacement and large time computation caused by extracting too many feature points. Taking the characteristics of the microscopic displacement experimental model into account, this method extracts the boundary of the image containing rich amount of information, and extracts feature points at the boundary of image. The feature points which meet special conditions are obtained by revised Hassion corner detection method. Experimental results illustrate that the proposed method can improve correct matching rate and reduce time computation at the same time.