A Method of Dividing Image Regions Based on RGB Variation Trends

Abstract

The invention discloses a method for dividing an image area based on the change trend of RGB, which mainly uses two rounds of similar judgments to divide the image area, and uses the similarity of the change direction of the RGB three primary color channels and the proximity of the physical position of the pixel to determine whether the pixel is a certain One of the area clustering, which belongs to an image preprocessing method. The method for dividing an image area based on the RGB change trend of the present invention can be judged according to the change trend of the color signal, which makes the edge division more clear and effectively improves the accuracy of the image area division.

Description

technical field [0001] The invention relates to the technical field of image object recognition preprocessing, in particular to a method for dividing image regions based on RGB variation trends. Background technique [0002] Image segmentation is a basic computer vision technology and a key step from image processing to image analysis. Effective and reasonable image segmentation can abstract very useful information for content-based image retrieval, object analysis, etc., thus making higher-level image understanding possible. But image segmentation is still a problem that has not been well solved so far, and it is still a hot research topic. [0003] Most of the existing image segmentation methods convert the image to be processed into a grayscale image, and use the direct difference of the grayscale value of the image to determine the similarity of the image pixels based on the threshold value, judge the image boundary, and divide the image Area. The more classic algorit...

AI Technical Summary

Problems solved by technology

The more classic algorithms include threshold-based segmentation (fixed threshold segmentation, adaptive threshold image segmentation, etc.), edge-based segmentation (Canny edge detection, etc.), region-based segmentation (seed region growth method, region splitting and merging method) etc.), etc., due to the lack of color information, these algorithms cannot distinguish regions with the same brightness but less obvious color changes, which makes edge detection inaccurate and results in inaccurate division of regions

Even if there are a few algorithms for area division based on color thresholds, a single color difference threshold is used as the judgment standard. This threshold selection ignores the influence of the local information of the image on the human eye's perception of color difference, and it is also difficult to judge the boundary. leading to inaccurate division of regions

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