一种基于图像插值运算的Laplace算子边缘检测方法
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摘要
对原有Laplace算子边缘检测方法进行改进以提高边缘检测的精度和清晰度。具体是通过对原图像进行插值运算扩展了原图像的大小,从而达到更精确的确定图像中边缘信息的目的;同时对原有的Laplace算子模板进行扩展,使得扩展后的模板能够同时检测多个方向的边缘信息。通过实验对比不同方法在不同图像场景中边缘检测的效果,可以发现本文所提出的边缘检测方法在一定程度上解决了原有Laplace算子所存在的问题,提高了边缘检测的效果。
The edge detection of the original Laplace operator is improved to increase the accuracy and sharpness of edge detection. The size of the original image is expanded by interpolating the original image. So as to achieve more accurate determination of the edge information in the image. At the same time, the original Laplace operator template is extended to enable the extended template to detect the edge information in multiple directions. By comparing the effect of different methods in different image scene of edge detection experiments, it can be found that the edge detection method proposed in this paper solves the existing problems of the original Laplace operator to a certain extent and improves the effect of edge detection.
The edge detection of the original Laplace operator is improved to increase the accuracy and sharpness of edge detection. The size of the original image is expanded by interpolating the original image. So as to achieve more accurate determination of the edge information in the image. At the same time, the original Laplace operator template is extended to enable the extended template to detect the edge information in multiple directions. By comparing the effect of different methods in different image scene of edge detection experiments, it can be found that the edge detection method proposed in this paper solves the existing problems of the original Laplace operator to a certain extent and improves the effect of edge detection.
引文
[1] J. Canny. A Computational Approach to Edge Detection. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1986, 8(6):679-698.
[2] Nieto, J. J and Torres. Approximation of solutions for nonlinear problems with an application to the study of aneurysms of the circle ofWillis. Nonlinear Analysis, 2000, 40(1):513-521.
[3] Y. Meng, Z. Zhang, H. Yin and T. Ma. Automatic detection of particle size distribution by image analysis based on local adaptive can-ny edge detection and modified circular Hough transform. 2018, 106:34-41.
[4]徐德明,万长林.可抗噪声的Canny改进边缘检测算法[J].计算机系统应用,2017,26(01):201-205.
[5] S. Nashat, A. Abdullah and M. Z. Abdullah. Unimodal thresholding for Laplacian-based Canny-Deriche filter. Pattern RecognitionLetters, 2012, 33(10):1269-1286.
[6]鲍宗泛,李红华.关于图像边缘检测的Laplace算子的改进[J].中国计量学院学报,2000(02):81-84.
[7]黄朝兵,黄创.图像边缘检测Laplace算子扩展的讨论[J].现代计算机,2006(10):76-77,83.
[8]黄剑玲,邹辉.基于高斯Laplace算子图像边缘检测的改进[J].微电子学与计算机,2007(09):155-157,161.
[2] Nieto, J. J and Torres. Approximation of solutions for nonlinear problems with an application to the study of aneurysms of the circle ofWillis. Nonlinear Analysis, 2000, 40(1):513-521.
[3] Y. Meng, Z. Zhang, H. Yin and T. Ma. Automatic detection of particle size distribution by image analysis based on local adaptive can-ny edge detection and modified circular Hough transform. 2018, 106:34-41.
[4]徐德明,万长林.可抗噪声的Canny改进边缘检测算法[J].计算机系统应用,2017,26(01):201-205.
[5] S. Nashat, A. Abdullah and M. Z. Abdullah. Unimodal thresholding for Laplacian-based Canny-Deriche filter. Pattern RecognitionLetters, 2012, 33(10):1269-1286.
[6]鲍宗泛,李红华.关于图像边缘检测的Laplace算子的改进[J].中国计量学院学报,2000(02):81-84.
[7]黄朝兵,黄创.图像边缘检测Laplace算子扩展的讨论[J].现代计算机,2006(10):76-77,83.
[8]黄剑玲,邹辉.基于高斯Laplace算子图像边缘检测的改进[J].微电子学与计算机,2007(09):155-157,161.