Hypergraph spectrum analysis based image segmentation method

An image segmentation and hyper-atlas technology, applied in image analysis, image data processing, instruments, etc., can solve problems such as large amount of calculation, unsatisfactory results, and inability to describe the complex relationship between image areas, and achieve accurate segmentation results and regional Consistency and edge accuracy improvements

Active Publication Date: 2014-01-29
NANJING UNIV OF INFORMATION SCI & TECH
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Problems solved by technology

[0013] 1) No unary (Unary) item is embedded, such as the priors of the respective graph nodes, which is equivalent to zero priors for all nodes;
[0014] 2) It is necessary to calculate the generalized eigenvector of a large matrix, although the complexity suppression measures are taken, the calculation is s

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  • Hypergraph spectrum analysis based image segmentation method
  • Hypergraph spectrum analysis based image segmentation method
  • Hypergraph spectrum analysis based image segmentation method

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[0038] The technical solutions provided by the present invention will be described in detail below in conjunction with specific examples. It should be understood that the following specific embodiments are only used to illustrate the present invention and are not intended to limit the scope of the present invention.

[0039] Such as figure 1 Shown, the present invention comprises the steps:

[0040] 1. Image preprocessing step: Based on a given image, at least two over-segmentation methods are used to over-segment the image respectively. The over-segmentation method divides the image into several sub-regions, and each sub-region is used as a superpixel to obtain superpixels. Pixel collection. Since a variety of over-segmentation methods are used, this step obtains a variety of over-segmented superpixel sets. The above over-segmentation methods include: Kmeans segmentation method, Meanshift segmentation method, hierarchical segmentation method based on contour detection, mult...

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Abstract

The invention discloses a hypergraph spectrum analysis based image segmentation method which specifically includes the steps of image preprocessing, image superpixel uniting, hypergraph model generation and hypergraph spectrum clustering. Areas after image over-segmentation are used as superpixels which are taken as vertexes, relation among the superpixels is obtained via various different over-segmentation methods to construct a hyperedge so as to form a hyperedge model, a traditional method for establishing relation (edge) between every two pixels to form a graph model is replaced, and accordingly high-order coupling relation among the pixels is reflected effectively, relevance among the areas of an image is considered, and area consistency and edge accuracy of a segmentation result are enabled to be obviously improved.

Description

technical field [0001] The invention belongs to the technical field of computer vision and image processing, and in particular relates to an image segmentation method based on hypergraph analysis. Background technique [0002] In the field of computer vision, image segmentation (Segmentation) refers to the process of subdividing a digital image into multiple image sub-regions. The purpose of image segmentation is to simplify or change the representation of images, which is the basic work in the field of image processing and computer vision, making images easier to understand and analyze. In reality, although humans can easily divide images into coherent regions, it is very difficult for computer vision systems. Although many segmentation methods have been proposed, due to the diversity and ambiguity of natural images, the performance of segmentation cannot meet the actual needs. [0003] At present, the number of image segmentation methods is very large, among them, method...

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Application Information

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IPC IPC(8): G06T7/00
Inventor 刘青山王灿田孙玉宝邓建康
Owner NANJING UNIV OF INFORMATION SCI & TECH
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