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出 处:《计算机应用》2014年第A01期196-198,共3页journal of Computer Applications
基 金:国家自然科学基金资助项目(61370166)
摘 要:针对Hough变换检测计算量巨大,而且检测结果含有大量虚假直线的问题,利用双色像素(TCP)与矢量内积过滤作为Hough变换输入的边缘点。将图像划分为若干子图,利用TCP算法得到每个子图中潜在的直线段;计算Canny边缘点的梯度方向;再计算边缘点梯度与其所在子图直线段方向矢量之间的内积,作为判定边缘点是否位于直线上的依据。为了提高算法的效率,可用CUDA并行分层算法加速TCP的计算。由于过滤了大量的边缘点,使得Hough变换的计算量大大减少,同时提高了Hough变换的直线检测准确度。实验表明,该算法可以高效、准确地检测出图像中的主要直线。In view of the large amount of calculation of the Hough transform, and the problem of lots of false straight lines contained in the detection result, a novel algorithm was proposed which used TCP ( Two-Colored Pixel) with vector inner product to filter the input edge-points of the Hough transform. Firstly, an image was divided into several subimages, TCP algorithms was used to get the potential straight segments in each subimage; secondly, the gradient direction of each edge- point detected by Canny operator was determined, and then the inner product of the gradient of each edge-point and its subgraph TCP-line's direction vector was calculated; the value of inner product for an edge-point was finally served as its determinant for whether it lied on a straight line. In order to improve the efficiency of the algorithm, CUDA parallel layered algorithm was exploited to accelerate the calculation of TCP. Because a large number of edge-points were filtered, the amount of calculation of the Hough transform was greatly reduced, and as a result the accuracy of straight line detection was also to be improved. Experiments show that the algorithm can efficiently and accurately detect the main straight lines of an image.
分 类 号:TP391.41[自动化与计算机技术—计算机应用技术]
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