kht_sandbox-1.0.2-source.zip下载

kht_sandbox是Kernel-based Hough transform(KHT)的算法实现以及c和matlab使用示例。KHT算法采用簇的投票机制加快霍夫变换的检测，近乎可以达到实时的要求，实测对于800*800的图像，KHT算法能达到25-40的帧率。 Fernandes and Oliveira suggested an improved voting scheme for the Hough transform that allows a software implementation to achieve real-time performance even on relatively large images (e.g., 1280×960). The Kernel-based Hough transform uses the same (r,\theta ) parameterization proposed by Duda and Hart but operates on clusters of approximately collinear pixels. For each cluster, votes are cast using an oriented elliptical-Gaussian kernel that models the uncertainty associated with the best-fitting line with respect to the corresponding cluster. The approach not only significantly improves the performance of the voting scheme, but also produces a much cleaner accumulator and makes the transform more robust to the detection of spurious lines.