Color image edge detection method

An edge detection and color image technology, applied in image enhancement, image analysis, image data processing, etc., can solve the problems of non-adaptive threshold and insufficient edge extraction accuracy

Pending Publication Date: 2022-02-08
HEILONGJIANG INST OF TECH
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Problems solved by technology

[0003] In order to solve the problem of insufficient edge extraction accuracy and non-adaptive threshold in the existing image

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Embodiment Construction

[0047] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0048] Cellular neural network (CNN) is one of the effective tools for image edge detection. It was proposed by Berkeley et al. in 1988. It is a large nonlinear circuit with real-time signal processing capabilities. It consists of a large number of units and only allows adjacent Direct communication between units, because it is easy to implement in VLSI hardware, has been widely used in image processing, pattern recognition, visual signal processing and simulatio...

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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...

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Application Information

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IPC IPC(8): G06T7/13G06T7/136G06N3/04
CPCG06T7/13G06T7/136G06T2207/10024G06T2207/20081G06T2207/20084G06N3/045
Inventor 张宪红穆卓嘉
Owner HEILONGJIANG INST OF TECH
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