A method and a system for carrying out super-pixel segmentation on an image

Abstract

The invention provides a method for carrying out super-pixel segmentation on an image, the image comprises one or more image blocks, and the method comprises the following steps: 1) determining the richness degree of color information contained in each image block for each image block; And 2) according to the richness degree of the color information contained in the image block, determining a coefficient alpha for a color distance and a coefficient beta for a spatial distance set for the image block in an SLIC algorithm. By means of the mode, when an SLIC algorithm is implemented, the influence of colors and pixel point positions on the segmentation result can be adjusted in a self-adaptive mode according to image characteristics. Through the test ratio, the better edge recall rate and thebetter under-segmentation error rate can be obtained at the cost of increasing very little operation time, that is, the edge loss can be better prevented by adopting the method provided by the invention, and the better edge fitting degree is obtained.

Description

technical field [0001] The present invention relates to image processing, in particular to image area division. Background technique [0002] With the development of science and technology, more and more applications require computers to replace human eyes to complete the operations of identifying, tracking, and long-term analysis of target areas in video frames. Different from the image background area, the target area is the hotspot that human eyes focus on. How to let the computer determine the target area is the key to this technology. [0003] Superpixel segmentation is the preprocessing to achieve operations such as object region segmentation, and has been widely used in computer vision applications such as image segmentation, pose estimation, and object recognition. It was first proposed in the article "Learning a Classification Model for Segmentation" published by Ren.X et al. in ICCV in 2003. Irregular pixel blocks of visual significance are used as a superpixel, ...

AI Technical Summary

Problems solved by technology

However, the traditional SLIC algorithm only considers the color features and distance position information between pixels, and cannot adaptively adjust the calculation strategy according to the characteristics of different images, resulting in the segmentation of the target area in some images with complex colors. The ideal effect cannot be achieved, and overflow or incomplete segmentation occurs, which affects the accuracy of subsequent target segmentation and extraction.

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