针对水下环境中传统算法对双目图像匹配时存在速度慢、误匹配较多等问题, 提出一种基于 ORB(的特征检测和曲线极线约束相结合的水下立体匹配方法。先检测图像的特征点, 生成描述子, 并进行特征匹配; 然后根据折射定律, 结合双目相机的内外参数, 推导出水下曲线极线; 最后结合水下曲线极线约束, 剔除误匹配点。实验结果表明, 相比传统的 SIFT算法与曲线约束, 论文提出的立体匹配方法在有效控制误匹配的情况下, 显著提高了运算速度, 对提升水下双目视觉系统的快速处理能力具有实践意义。

Since the traditional algorithm may cause problems such as slow running speed and more mismatching points when perform stereo matching on underwater environment, the ORB characteristics detection and curve re-striction has been applied in this paper. Firstly the image should be detected so as to find out the characteristics, generate the descriptor, and match the feature points. Then the underwater curve restriction can be deduced ac-cording to the law of refraction combining internal and external parameters of camera. Finally the mismatching points can be decreased by means of underwater curve restriction. The experimental results have shown that in the case of effectively controlling mismatches, the speed of this algorithm are faster than traditional SIFT algorithm combined with curve restriction. As a result, it is of practical significance to improve the speed of underwater binocular vision system.