Color image segmentation method integrating region growth and edge detection

Abstract

The invention provides a color image segmentation method integrating region growth and edge detection. The color image segmentation method comprises the steps that an image to be segmented is input; the image is converted into a gray level image, and according to a Canny edge detection algorithm, edge detection is conducted with the maximum between-cluster variance threshold value obtained through the Otsu method as a high threshold value; the image is converted into an RGB color image, the maximum Euclidean distance between one point and all points of an eight neighborhood of the point is calculated, and if the maximum Euclidean distance is smaller than a regulated threshold value, the point can be used as a candidate seed point; seed selection is completed, if one point is the candidate seed point obtained in the step (2) but not the edge point obtained in the step (1), the point can be used as an initial seed point; growth is conducted on a seed area according to a growth rule, and pixel points according with the growth rule are classified into the seed area; area blocks, which are adjacent in the space and accord with an area combination rule, in the image are combined according to the area combination rule; the steps are executed repeatedly until an area combination stopping condition is met; color image segmentation is completed.

Description

technical field [0001] The invention relates to a color image segmentation method used in the field of digital image processing, in particular to a color image segmentation method combining region growing and edge detection. Background technique [0002] Image segmentation is to extract the region of interest from the image. In the past research, the segmentation of monochrome images was the main research direction. However, not all monochrome images are used in daily life, and the segmentation of color images has attracted more and more people's attention along with the substantial increase in computer processing speed and the development of real life. Monochrome image segmentation only focuses on the only available information of brightness (Lightness), while color images contain effective information such as brightness, hue, and color depth. Obviously, color images have more information than monochrome images. Therefore, the segmentation of color images is in line with ...

AI Technical Summary

Problems solved by technology

[0005] The present invention overcomes the shortcomings of poor segmentation accuracy in the prior art, and proposes a color image segmentation method that combines region growing and edge detection, aiming at improving segmentation accuracy and providing a reliable basis for subsequent target recognition and image analysis

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