Interactive image segmentation method for multiple foreground targets

Abstract

The invention provides an interactive image segmentation method for multiple foreground targets. The method comprises the following steps of: performing linear reconstruction on pixel colors in an image local window, and repeatedly modifying color reconstruction coefficients by using linear projection; repeatedly performing the linear reconstruction on pixel class label vectors in the image localwindow by using the modified color reconstruction coefficients, and estimating to acquire local reconstruction errors; accumulating the local reconstruction errors to acquire a global reconstruction error; building an interactive image segmentation model of the multiple foreground targets; and performing cluster analysis on the same class of pixels which are labeled by a user to acquire a clustering center; acquiring a group of polynomial functions by adopting regression estimation by taking the clustering center as a training sample; mapping the unlabelled pixels by using the polynomial functions to acquire an initial solution; solving the segmentation model; and determining the class attribution of the unlabelled pixels, and outputting a segmentation result. The interactive image segmentation method has a wide application prospect, and the problem that the multiple foreground targets are difficult to segment simultaneously in the prior art is solved.

Description

technical field [0001] The present invention relates to technical fields such as image processing and pattern recognition, and in particular to an interactive image segmentation method for multiple foreground targets based on multiple linear reconstructions of image pixel category label vectors and pixel category label vector regression. Background technique [0002] Image segmentation refers to separating the visual target of user interest from the image background, thereby dividing the image into multiple disjoint sub-regions. Image segmentation can provide the basis for subsequent image processing tasks such as visual target tracking, target classification, and target editing. It has very important applications in various industries such as digital entertainment, medical image processing, video surveillance, industrial inspection, military and sports. [0003] After decades of research, image segmentation technology has been greatly developed. However, there is currently...

AI Technical Summary

Problems solved by technology

This method of segmenting only one foreground object at a time will inevitably require more user participation and longer user waiting time

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