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Line detection algorithm based on random sample theory

机译:基于随机样本理论的线检测算法

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摘要

Hough transform is a traditional algorithm for line detection. But this algorithm has many disadvantages, such as large computing load, long operating time, large occupied memory and low precision. This paper forwards a new line detection algorithm, that is, detecting line based on random sample theory. This algorithm can solve the problems brought by Hough transform. In this paper, at first, the steps of both Hough transform algorithm and random sample line detection algorithm are listed respectively and the latter one is discussed in detailed. Then, the two algorithms are tested by the simulative experiments. The results of these experiments are compared and analyzed. At last, the result of the experiment using real image is displayed.
机译:霍夫变换是用于线检测的传统算法。但是该算法具有计算量大,运算时间长,占用内存大,精度低等缺点。提出了一种新的线检测算法,即基于随机样本理论的线检测。该算法可以解决霍夫变换带来的问题。本文首先分别列出了Hough变换算法和随机样本线检测算法的步骤,并详细讨论了后者。然后,通过仿真实验对这两种算法进行了测试。比较了这些实验的结果。最后,显示使用真实图像的实验结果。

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