SURF算法的降维研究.PDFVIP

2017 年 软 件 2017, Vol . 38, No . 12 第 38 卷 第 12 期 COMPUTER ENGINEERING SOFTWARE 国际 IT 传媒品牌 设讨研尧与启用 SURF算法的降维研究 卢清薇，罗旌钰，王云峰 (厦门大学厦门大学电子工程系，福建厦门361005 ) 摘 要 ：SURF(Speed-up robustfeatures )算法进行图像特征点匹配时需要循环遍历待匹配图像所有特征点，计 特征点之间的SURF64描述距离，耗时大。本文对SURF算法进行了 16维与4 维的降维研究。实验结果表明，16 维 SURF算法性能与64维 SURF算法基本相当，但能大幅度降低运算时间；4 维运算性能降低较大，不能用于特征 点匹配，但4 维 SUFR描述算法可以扩展到图像的各个像素点，用于IC P算法及图像的稠密匹配。 关键词：图像匹配；特征点；SURF算法；降维 中图分类号：TP391 文献标识码 ：A D O I ： 10.3969/j .issn .1003-6970.2017.12.028 本文著录格式：卢清薇，罗旌钰，王云峰.SURF算法的降维研究J ].软件，2017, 38 (12): 148-152 Research on Dimensional Reduction for SURF Algorithm LU Qing -wei , LUO Jing -yu , Wang Yun-feng (Departm ent o f electronic engineering , Xiam en U niversity , Xiam en F u jia n 361005, C hina ) 【A b stract 】 ：Matching image feature point by SURF(Speed-up robust features) algorithm needs to loop through all feature points on the image to be matched , and compute the sixty-four dimensional distance of SURF between fea­ ture points , which will take a long computation time . The sixteen dimensional SURF and four SURF are imple­ mented. The experimental results show that the performance of the sixteen dimensional SURF is almost the same as that of the sixty-four dimensional SURF , moreover the sixteen dimensional SURF takes less time than sixty-four dimensional SURF. The performance of four dimensional SURF is much inferior to that of sixty-four dimensional SURF , so it cannot used to match feature point . However the four dimensional description of SURF can be ex ­ panded to all feature points , which can be applied in ICP algorithm and dense matching algorithm.