Method for edge detection of digital image

Abstract

The invention discloses a method for edge detection of a digital image, so that a technical problem that a current Canny operator edge detection method is restricted by a selected threshold can be solved. According to a technical scheme employed in the invention, a gray value matrix of an image is obtained and gray values are normalized to an interval [0, 1]; the size of a template is defined and memberships um (x (i, j)) of all pixels in the template are calculated according to a membership function; and fuzzy entropies of all pixels in a window are calculated according to a fuzzy entropy formula, and fuzzy entropy information measure is calculated and is compared with a threshold so as to determine whether there is a boundary. Because a pixel point in the template is used as a processing unit and a fuzzy algorithm is utilized, noises in a filtered image are reduced and a fuzzy phenomenon existing in the filtered image is significantly improved. Compared with a threshold segmentation method in a background technology, the provided method has the following advantages: there is no need to select a threshold; an error rate of a segmented image is low; and a visual effect of the image can be substantially improved.

Description

technical field [0001] The invention relates to an edge detection method, in particular to a digital image edge detection method. Background technique [0002] The document ""Digital Image Processing" edited by He Mingyi" discloses an edge detection method using the Canny operator. The specific steps are: [0003] (1) Select a Gaussian filter to smooth the image to remove noise. [0004] (2) Calculate the gradient of the smoothed image using the finite difference of the first-order partial derivative. [0005] (3) Only obtaining the global gradient is not enough to determine the edge. In order to determine the edge, the above gradient must be suppressed by non-maximum value. The specific method is to find the local maximum value point in the image gradient and set the non-local maximum value A value of zero makes the edges of the image thinner. [0006] (4) Detect and connect edges with a double-threshold algorithm. [0007] The key to using the Canny operator to detect ...

AI Technical Summary

Problems solved by technology

[0007] The key to using the Canny operator to detect image edges is to select an appropriate threshold. If the high threshold is set too small, the detected edge will be mixed with a lot of noise, and if it is set too large, the real edge will be missed. For a low threshold , if the setting is too large, the edge with a small gray value mutation will be missed; in addition, a reasonable filter size is also very important. The larger the size of the filter, the greater the smoothness of the image, which will lead to the disappearance of image details and the sudden change of gray value. It will also be far away from the original edge position, and at the same time make the length of the Gaussian filter longer and increase the amount of calculation. On the contrary, the detected edge will be mixed with a lot of noise because the image is not smooth enough.

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