改进SIFT算法实现图像的快速匹配

Fast image match with an improved efficient SIFT algorithm

为解决图像匹配耗时的问题,提出一种改进的图像匹配方案.在尺度不变特性变换(SIFT)算法的基础上,以特征点邻域灰度值的差熵大小来筛选稳定特征点,减少所需描述及匹配的不稳定特征点的数量,提高算法匹配效率.同时,改进误匹配去除算法,以大幅提高误匹配去除效率.实验结果表明,与SIFT及RANSAC相结合的图像匹配方案,或相关的改进方案相比,本方案可最大程度地保存最终匹配的特征点数量,并提高特征点匹配的实时性、匹配率及正确匹配率.

An improved image matching method has been proposed to accelerate the image matching procedure based on SIFT algorithm. First,an entropy-based approach to filter out the unstable featurepoints from the candidates is proposed. It can reduce the unstable ones during the feature descriptor computing and matching stages. Second,a fast mismatching-removing method,which highly improve the efficiency of eliminating the small quantity of remaining mismatching points,is proposed. A serial of experiments are conducted which demonstrate that the proposed approaches have a better accuracy,real-time than other improved methods.