Lateral inhibition random fractal search template coupling method

Abstract

The present invention discloses a lateral inhibition random fractal search template coupling method. The method comprises: performing image preprocessing, obtaining an original image and a template image, and converting the original image and the template image to a gray level mode; utilizing the lateral inhibition mechanism to perform image processing, wherein the inhibition mechanism can effectively perform background inhibition and target enhancement so as to reduce the image noise and improve the signal to noise ratio; performing LI-SFS parameter initialization; setting the maximum number of diffusion times as 1; applying the Gaussian migration method to solve the template matching problem updating the position of a search individual; and obtaining an optimal individual after performing the update process twice. The lateral inhibition random fractal search template coupling method is compared with the algorithm based on the lateral inhibition, and the experiment result is shown in the template matching problem. The lateral inhibition random fractal search template coupling method has good effect and robustness, is greatly helpful to detect a target in the cluttered background, can enhance the comparison of the feeling information and reduce the low-frequency noise.

Description

technical field [0001] The invention belongs to the technical field of image processing, in particular to a side suppression random fractal search template matching method. Background technique [0002] Template matching refers to the process of finding the same or similar region as a given template in the target image. It is one of the basic methods of computer vision and has been widely used in many fields such as face recognition, lung nodule detection, handwriting recognition and road detection. Applications. Template matching techniques involve translating the template to each possible location in the original image, and evaluating the match between the template and the original image at that location. Template matching methods are mainly divided into two categories: matching based on grayscale methods and matching based on feature methods. The matching based on the grayscale method is based on the grayscale value, and the partial similarity between the template and t...

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Problems solved by technology

[0004] The purpose of the present invention is to provide a random fractal search template matching method with lateral suppression, aiming to solve the problem of falling into a local optimum in the process of searching for the optimal matching solution, resulting in the search stagnation of the entire group, and the limitation of the feasible region search space in the matching process. Discrete and oscillating, so that the search algorithm is prone to fall into a local optimum and cause the search stagnation problem of the entire group

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