摘要
针对视觉导航中存在的图像特征点提取精度与用时之间的矛盾,对几种常用的特征点提取算法(Harris,SIFT,SURF)进行了论述,并针对SIFT算法和SURF算法进行了比较,同时搭建了四旋翼验证平台,利用四旋翼实验平台,针对自然环境中的实物测试了上述两种算法的提取精度与用时,结果表明SURF算法是视觉导航中综合考虑匹配的正确率及实时性的较优选择.
Several feature points extraction methods such as Harris, SIFT and SURF were de- scribed. SIFT and SURF methods were mainly compared in order to find a better solution for the contradictions between extraction precision and extraction consuming time in vision navi- gation. A quadrotor verification platform integrating was built to test extraction precision and extraction consuming time of SIFT and SURF methods in the natural environment. The comparison result shows that SURF was the suitable method which can meet the requirements of extraction precision and real time simultaneously.
出处
《哈尔滨商业大学学报（自然科学版）》
CAS
2015年第1期61-64,共4页
Journal of Harbin University of Commerce：Natural Sciences Edition
