基于特征和区域的图像匹配方法  

A Region-Based Image Matching Algorithm Combining Global and Local Features

作　　者：侯静[1] 李孟歆[1] 赵岚光[1] 张凤众[1] 

机构地区：[1]沈阳建筑大学信息与控制工程学院,辽宁沈阳110168

出　　处：《沈阳建筑大学学报（自然科学版）》2012年第2期380-384,共5页Journal of Shenyang Jianzhu University：Natural Science

基　　金：国家自然科学基金项目(60874103);住房和城乡建设部基金项目(2007-K4-9)

摘　　要：目的研究一种新的图像匹配方法,解决目前图像匹配中由于背景差异变化较大造成的匹配精度低、匹配效果不理想等问题.方法设计了一种综合全局和局部特征、基于区域的级联匹配策略,首先对分割区域的全局特征进行快速匹配,其次在快速匹配的结果基础上进行Affine-SIFT算符的匹配,并在匹配中利用随机抽样一致性(RANSAC)过滤错误匹配.结果采用级联匹配策略,综合全局特征匹配的快速性和局部特征描述子的不变性,先确定图像之间的最优匹配区域再进行图像匹配,提高了匹配效率.结论解决了图像尺寸变化较大时匹配精度低的问题,过滤了错误匹配结果,得到了较高的精度,且大大减少了计算量,在一定程度上提高了计算速度.A new approach is presented to match two images in presenting large scale changes. The novelty of our algorithm is a hierarchical matching strategy for global region features and local descriptors, which combines the descriptive power of global features and the discriminative power of local descriptors. To predict the likely location and scale of an object, global features extracted from the segmentation regions are used in the first stage for an efficient region matching. This initial matching can be ambiguous due to the instability and unreliability of global region feature, and therefore in the later stage local descriptors are matched within each region pair to discard false positives and the final matches are filtered by RANSAC. Experiments show the effectiveness and superiority of the proposed method in comparing to other approaches.

关 键 词：图像匹配 级联匹配策略 全局特征 局部描述 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]