Robustness image segmentation algorithm based on low rank recovery

An image segmentation and robust technology, applied in the field of image processing, can solve the problems affecting the quality of image segmentation and image subsequent processing, and achieve accurate segmentation and high-quality results.

Inactive Publication Date: 2016-08-24
WUHAN INSTITUTE OF TECHNOLOGY
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Problems solved by technology

[0005] The present invention provides a robust image segmentation algorithm based on low-rank recovery, which solves the technical problems in the prior art that noise affects the quality of image segmentation and the subsequent processing of images

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  • Robustness image segmentation algorithm based on low rank recovery
  • Robustness image segmentation algorithm based on low rank recovery
  • Robustness image segmentation algorithm based on low rank recovery

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Embodiment Construction

[0031] The embodiment of the present application provides a robust image segmentation algorithm based on low-rank recovery, which solves the technical problem in the prior art that noise affects the quality of image segmentation and the subsequent processing of images; it achieves avoiding the impact of noise and improving image segmentation Quality technical effects.

[0032] In order to solve the above technical problems, the general idea of ​​the technical solution provided by the embodiment of the present application is as follows:

[0033] A robust image segmentation algorithm based on low-rank recovery, characterized in that: the low-rank space decomposition is used to obtain a feature space image, and the feature space image is segmented by a graph cut method based on minimum cut / maximum flow; comprising the following steps:

[0034] The image to be processed is divided into overlapping image blocks, and the image blocks are converted into a column vector matrix accordi...

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Abstract

The invention belongs to the field of image processing technology, and discloses a robustness image segmentation algorithm based on low rank recovery. The invention is characterized by obtaining a feature space image using a low rank space decomposition and segmenting the feature space image through an image segmentation method based on min-cut / max-flow; and by including the steps of: dividing an image to be processed into overlapping image blocks and converting the image blocks into a column vector matrix according to positions of the overlapping blocks; processing the column vector matrix of the image blocks using a low rank matrix recovery method to obtain a feature space image; and segmenting the feature space image through the image segmentation method based on min-cut / max-flow. The invention extracts more image edge information through low rank space recovery in such a manner that the image tag is more accurate and the segmentation quality of the image is improved. The invention overcomes the impact of noise points on the segmentation quality.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to a robust image segmentation algorithm based on low-rank restoration. Background technique [0002] Image segmentation is the basis of image processing and computer vision. Image segmentation is to divide the image into non-overlapping regions, realize the separation of the target and the background of the image, and facilitate the subsequent reconstruction and recognition of the image. In various application scenarios of computer vision, the quality of image segmentation affects the subsequent processing of images. Image segmentation quality is closely related to the accuracy of its edges. More and more novel segmentation methods for image segmentation have been proposed and applied to various aspects of the field of computer vision. [0003] There are many methods for image segmentation. The edge-based method mainly uses the gradient operator to detect the edge of t...

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Application Information

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IPC IPC(8): G06T7/00
CPCG06T2207/20021
Inventor 万永静卢涛张彦铎李晓林杨威管英杰潘兰兰
Owner WUHAN INSTITUTE OF TECHNOLOGY
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