关键词: 机器人视觉, 目标识别, 图像匹配, 基础矩阵估计算法

Abstract: To guarantee the celerity and accuracy of identification,an improved algorithm of fundamental matrix estimation was proposed for image matching.Several algorithms were integrated to obtain more accurate match points,and sub-pixel Harris corner detection was applied to extract match point.Based on difference sum theorem,the normalized cross-correlation method was adopted to make coarse matching,and the fast clustering method was used to filter match points.After that,a random sampling method in Statistics was introduced to optimize the matching points and improve Hartley 8 point's method,which was a common method to estimate fundamental matrix.By taking the standard image as the object and the average pole distance as the evaluation index,the proposed algorithm was compared with other commonly used methods.The matching and positioning experiments for an actual target verified the effectiveness of the proposed algorithm in matching speed and accuracy of positioning.

Key words: robot vision, target recognition, image matching, fundamental matrix estimation algorithm