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An efficient connectivity-number-based edge detection method for binary images

机译:一种有效的基于连通性数的二值图像边缘检测方法

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A novel binary images edge detection method is presented. It directly clear the inner pixels of the images to obtain the edges. Connectivity-number were sought as detectors, those pixels that have zero-connectivity-number were eliminate as inner pixels from the image. Seventeen well-chosen templates change the computing into efficient exclusive or operations. Experimental results show that it provides less than 2-pixel-wide edges, spends average 8ms on the standard 256-by-256 Lena image. Considered the ratio of details and time consumed, the method shows improved performance than the well known Canny, Roberts and Sobel methods on binary images, and shows potential application on real-time edge detection for binary images.
机译:提出了一种新颖的二值图像边缘检测方法。它直接清除图像的内部像素以获得边缘。寻求连通性数作为检测器,将具有零连通性数的那些像素从图像中去除为内部像素。十七种精心挑选的模板将计算变为高效的异或运算。实验结果表明,它提供的边缘宽度不到2个像素,在标准256 x 256 Lena图像上平均花费8毫秒。考虑到细节和消耗的时间之比,该方法在二进制图像上的性能优于众所周知的Canny,Roberts和Sobel方法,并且在二进制图像的实时边缘检测中具有潜在的应用。

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