基于Zernike矩的亚像素边缘检测算法
首发时间:2014-11-03
摘要:针对传统算子定位精度较低、检测出的边缘较粗的缺点,本文提出了基于Zernike矩的亚像素边缘检测算子,并推导出 的模板系数。该算法采用积分算子的形式对噪声不敏感,能有效的抑制噪声,较好的提取出图像边缘并实现较高的定位,有效克服了传统算子如Sobel算子进行边缘检测时检测的边缘较粗,误差较大,以及对噪声敏感的缺点。实验结果证明,相比Sobel算子Zernike矩算子能够实现精确定位,并且其边缘检测精度能够达到亚像素级。
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Algorithm about Subpixel Edge Detection of Image Based on Zernike moments
Abstract:Aim to the drawbacks of traditional algorithms that have lower location precision and detect wider edge, the sub-pixel edge detection operator which based on Zernike moments were proposed in this paper. Moreover, a mask of size seven by seven was caculated. The algorithm is in the form of integral operator which is not sensitive to noise, resulting in effectively suppresses noise, detects the better edge of image and achieves higher localization. It can overcome the disadvantages of traditional algorithms such as Sobel operator that detects the edge in thicker, larger error and is more sensitive to noise. Compared to Sobel operator, the results of the experiment verify that the Zernike moments can precise positioning. Moreover, the accuracy can reach the level of sub-pixel.
Keywords: Zernike moments sub-pixel edge detection
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