Color image edge detection method

Abstract

The invention provides a color image edge detection method. The method comprises the following steps of 1, inputting a color image and carrying out normalization processing on the input original image; 2, analyzing the monostable characteristic of the FHN, constructing an adjustment function to optimize a diffusion coefficient in a reaction diffusion equation according to the gray level change of a local region, and calculating a threshold value with gray level self-adaption; 3, constructing a cellular neural network structure based on a FitzHugh-Nagumo (FHN) reaction diffusion equation; 4, performing edge detection on a gray color image or a color image in an HSV color space by using the proposed cellular neural network model; and 5, outputting an edge detection result of the color image. According to the method, the dynamic property of the FHN reaction diffusion equation is analyzed, and feasibility of the FHN reaction diffusion equation in image edge extraction is proved; the CNN based on the FHN reaction diffusion equation is applied to edge detection of gray and color images; the diffusion coefficient is optimized by adopting the reaction diffusion equation, so the threshold value is more adaptive, and the adaptive threshold value can be adaptively selected according to brightness of the color image, so the provided color image edge detection method is effective.

Description

technical field [0001] The invention belongs to the technical field of image segmentation, in particular to a color image edge detection method based on a reaction-diffusion equation. Background technique [0002] Edge detection is a classic problem in the field of image processing, especially color image edge extraction has always been a hot issue in the field of image processing. Compared with grayscale images, the edge detection results of color images will contain more edge information, especially for some images with the same brightness but different colors. In recent years, many scientists have done a lot of research in this field. Some are about the optimization of classic algorithms, such as Sobel operator, Canny algorithm, etc. Although these technologies have been optimized on the original basis, they have not fundamentally solved the inherent shortcomings of these methods, such as insufficient edge extraction accuracy, Thresholds cannot be adaptive, etc. In add...

AI Technical Summary

Problems solved by technology

[0003] In order to solve the problem of insufficient edge extraction accuracy and non-adaptive threshold in the existing image segmentation technology, the present invention proposes a color image edge detection method based on reaction-diffusion equation

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