Image processing method and device

Abstract

The invention provides an image processing method and device suitable for the field of image processing. The method comprises that an original image is obtained; a first selection instruction is received, a first pixel set assigned by the first selection instruction is obtained from the original image, and a first Gaussian mixture model is established for the first pixel set; a second selection instruction is received, a second pixel set assigned by the second selection instruction is obtained from the original image, and a second Gaussian mixture model is established for the second pixel set; and a foreground side weight is determined according to the first Gaussian mixture model, a background side weight is determined according to the second Gaussian mixture model, a maximum-flow minimum-cut model is established according to the determined foreground side weight and background side weight, and a foreground of the original image is determined according to the established maximum-flow minimum-cut model. Compared with an image segmentation manner combining K-means algorithm and maximum-flow minimum-cut algorithm, the method can be used to extract the foreground from the original image more accurately by fully utilizing each obtained pixel.

Description

technical field [0001] The invention belongs to the field of image processing, in particular to an image processing method and device. Background technique [0002] Image segmentation predetermines the specific features of interest, extracts the area with the specific features from the original image, and takes the extracted area as the foreground. The existing image segmentation methods mainly include the following categories: threshold-based segmentation methods, region-based segmentation methods, edge-based segmentation methods, and segmentation methods based on specific theories. [0003] At present, the hottest image segmentation method combines hard clustering algorithm (K-means algorithm) and maximum flow minimum cut algorithm. In specific applications, the user draws the operation track in the target area of ​​the original image by operating the pen with the mouse or touch, and selects the pixels in the area from the original image according to the area passed by th...

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to provide an image processing method and device to solve the problem that the determined foreground is not accurate enough for image segmentation by combining the K-means algorithm and the maximum flow minimum cut algorithm

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