提出了一种基于迭代动态规划的双目Helmholtz立体视觉算法，并将其应用于高光物体的测量。算法首先对获取的Helmholtz图像对作图像校正，然后确定扫描线的端点，最后设计了一种迭代动态规划方法建立匹配获取视差图，从而恢复出高光物体的表面深度。实验采用光线跟踪方法获取带有高光的双目Helmholtz图像，视差图结果表明该方法能够有效地恢复出高光物体的深度信息。

A binocular Helmholtz stereo algorithm based on iterative dynamic programming method is proposed here and applied for measuring objects with highlights. In this algorithm, we first rectify the Helmholtz reciprocal image pairs. Then the end points of matching segments are detected. Lastly an iterative dynamic programming matching method is proposed to search for the matching points and reconstruct the depth of surface. Ray-tracing binocular Helmholtz images with highlights are used in our experiment and the disparity results show its good performance for reconstructing objects with highlights.