Abstract
For improving the processing speed and accuracy of edge detection, an adaptive edge detection method based on improved NMS (nonmaximum suppression) was proposed in this paper. In the method, the gradient image was computed by four directional Sobel operators. Then, the gradient image was processed by using NMS method. By defining a power map function, the elements values of gradient image histogram were mapped into a wider value range. By calculating the maximal between-class variance according to the mapped histogram, the corresponding threshold was obtained as adaptive threshold value in edge detection. Finally, to be convenient for engineering application, the proposed method was realized in FPGA (Field Programmable Gate Array). The experiment results demonstrated that the proposed method was effective in edge detection and suitable for real-time application.
Highlights
Due to the broad application fields, such as in industry, spaceflight, medicine, and military [1,2,3], the study on edge detection became a hot issue in image processing
For application in engineering fields, the proposed method was realized in FPGA
Where σB2 is the between-class variance, N is the total number of pixels of NMS processed gradient image, u is the average gradient amplitude, N1 is the number of edge points, and u1 and u2 are the average values of edge points and background points, respectively, in the mapped gradient image
Summary
Due to the broad application fields, such as in industry, spaceflight, medicine, and military [1,2,3], the study on edge detection became a hot issue in image processing. Many improved edge detection algorithms based on gradient calculation such as Roberts operator [8], Sobel operator [9], Canny operator [10], and Laplacian operator [11] were proposed successively. Wiehle and Lehner [14] proposed an edge detection algorithm for high definition satellite images based on Sobel operator. Li et al [19] designed a data block accelerator to optimize the Sobel operator in FPGA, and this method could be applied in real-time edge detection. An adaptive edge detection algorithm based on the NMS was proposed. In this method, the gradient image was processed by utilizing NMS method.
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