Image automatic segmentation method based on graph cut

An automatic segmentation and graph cutting technology, which is applied in the field of image processing, can solve the problem that the seed point cannot obtain the correct result, and achieve the effect of avoiding estimation and learning, good clustering, and accurate calculation of similarity

Inactive Publication Date: 2010-09-22
XIDIAN UNIV
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Problems solved by technology

[0016] 4) The quality of segmentation has a lot to do with the selection of seed points and the distribution estimation model of the data. Improper seed points cannot obtain correct results, and the selection of seed points has great differences depending on different people and situations. difference
Moreover, interactive segmentation often cannot quickly obtain good segmentation results, and the user needs to further carefully correct the segmentation results to obtain satisfactory results.

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  • Image automatic segmentation method based on graph cut
  • Image automatic segmentation method based on graph cut
  • Image automatic segmentation method based on graph cut

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Embodiment Construction

[0044] The present invention will be described in further detail below with reference to the accompanying drawings.

[0045] Refer to attached figure 1 , the implementation steps of the present invention include as follows:

[0046] Step 1: Initialize the object to be segmented.

[0047] (1a) Input the image I to be segmented, and set the number of rows of the image as r, the number of columns as c, take the center of the image to be segmented as the center, and take min(r / 6, c / 6) as the radius. A closed contour curve C is formed on the image, and the closed contour curve C divides the image whose definition domain is Ω into internal and external regions: C i and C o ,Ω=C i ∪C o ∪C;

[0048] (1b) Classify the initial closed curve C and the pixels in the inner area of ​​C into one category, denoted as C i ; Classify the pixels in the outer area of ​​the curve C into one category, denoted as C o ,like figure 2 , where the white area belongs to one class, indicating the...

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Abstract

The invention discloses an automatic segmentation method based on graph cut for color images and gray level images, mainly solving the problems of the existing graph cut technology that interaction and modeling are required in graph cut and the segmentation result is required to be modified manually. The method comprises the following steps: dividing an image into an inner area and an outer area; establishing the data item of the energy function according to the similarity of pixels in different areas, wherein mean shift, YCbCr color space conversion and block partition are adopted in calculation of the similarity; establishing the smoothing item of the energy function according to the marginal information and spatial location of the image; adopting graph cut to perform optimization to the energy function, thus realizing one-step cutting to the image; and using the segmentation result as the new inner and outer areas, performing iterative execution of the above operations, and stopping iterative execution when iterative conditions are satisfied. The method has the advantages of automation, good effect and less iterations and can be used in the computer vision fields such as image processing, image editing, image classification, image identification and the like.

Description

technical field [0001] The present invention relates to the field of image processing, specifically an image segmentation method, which can effectively segment color images and grayscale images into two parts, target and background, which can be used for subsequent image processing, recognition, and classification etc. provide the basis. Background technique [0002] Image segmentation is a fundamental and critical problem in the field of image processing and computer vision. The purpose of its segmentation is to extract the target of interest from the image background, and provide the basis for subsequent analysis, understanding, classification, tracking, identification and processing. Image segmentation is widely used, such as: medicine, image processing, military, sports, intelligent transportation, industry and agriculture, etc. It is used in almost all fields related to image processing. Because of the importance of image segmentation, the research on image segmentati...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00
Inventor 郭宝龙侯叶
Owner XIDIAN UNIV
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