Image segmentation method based on structure tensor and image segmentation model

Abstract

The invention discloses an image segmentation method based on a structure tensor and an image segmentation model, and belongs to the field of digital image processing. The method comprises the steps: taking an image as a hypersurface of a three-dimensional Euclidean space according the viewpoint of Riemannian geometry, and obtaining a classic ST (structure tensor); combining the obtained ST with the color information of the image, and obtaining an EST (extended structure tensor); carrying out the dimension reduction of the obtained EST through employing PCA, and obtaining a constrictive CST; carrying out the non-linear diffusion of the obtained CST through employing a vectorization mode of a PM equation; calculating the KL distance of two tensor spaces; substituting the obtained distance into a GrabCut model, and completing the segmentation of the image. The method is small in number of parameters, is simple in calculation, is high processing speed, is good in image segmentation effect, and is suitable for a condition that a to-be-segmented object is highly similar to the background.

Description

technical field [0001] The invention is an image segmentation method based on a structure tensor and a graph cut model, belonging to the field of digital image processing. Background technique [0002] Image segmentation is a basic research problem in the field of digital image processing and computer vision. By dividing the image into several non-overlapping sub-regions or smooth closed curves, and each sub-region or closed curve has a special meaning, therefore, it Become the research foundation of image analysis and visual computing. As a main way for people to recognize and understand external things in social production, visual activities mainly perceive objects from three aspects: shape, color and texture. However, as a basic attribute that widely exists on the surface of objects in nature, texture reflects the roughness, directionality and regularity of the surface of objects, and is one of the important characteristics for people to describe and identify different o...

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to find a texture extraction method based on the structure tensor, and combine it with color information, and introduce it into the GrabCut graph cut model to solve the problems of large amount of calculation and complicated parameter setting in the traditional texture extraction method, and propose An interactive image segmentation algorithm with good accuracy and robustness, realizing accurate segmentation of color texture images

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