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A New Concentric Circle Detection Method Based on Hough Transform

机译:一种基于Hough变换的新同心圆检测方法

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A new approach of concentric circle detection is proposed in this paper. Firstly, the image is preprocessed by denosing, edge detection, and then the circle centers are allocated by the gradient Hough transform, at last, the radius are detected by the improved one-dimensional Hough transform. The detection efficiency is enhanced by image discretization and reduced resolution ratio in the process of circle center detection, and proves that the circle center is on the gradient line of circle edge points; meanwhile, the radius detection accuracy is improved by merging the similar radius in the process of radius detection. Experimental results show that the method combined with gradient Hough transform and one-dimensional Hough transform has good reliability and is high adaptive to noise, distortion, area of incomplete, edge discontinuous. Analysis shows that this new concentric circle detection algorithm reduces time complexity and improves anti-interference compared with the traditional concentric circle detection algorithm based on chord mid-point Hough transforms.
机译:本文提出了一种同心圆检测的新方法。首先,通过抛弃,边缘检测来预处理图像,然后通过梯度霍夫变换分配圆心,最后,通过改进的一维霍夫变换来检测半径。通过图像离散化和圆形中心检测过程中的分辨率减少来提高检测效率,并证明圆中心位于圆形边缘点的梯度线上;同时,通过在半径检测过程中合并类似的半径来提高半径检测精度。实验结果表明,该方法与梯度霍夫变换相结合,一维霍夫变换具有良好的可靠性,高度适应噪音,失真,不完整区域,边缘不连续。分析表明,与基于弦中间点霍夫变换的传统同心圆检测算法相比,这种新的同心圆检测算法减少了时间复杂性并提高了抗干扰。

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