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Level set image segmentation method based on local guide core-fitting energy model

A technique of locally guiding kernels and energy models, applied in the field of image processing, which can solve problems such as complex grayscale unevenness, time-consuming, poor image effects, etc.

Inactive Publication Date: 2015-08-26
EAST CHINA UNIV OF TECH
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Problems solved by technology

These methods are all improved on the basis of variational theory, and image segmentation methods of different models are proposed, but these models are not effective in segmenting complex grayscale uneven images and are very time-consuming.

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  • Level set image segmentation method based on local guide core-fitting energy model
  • Level set image segmentation method based on local guide core-fitting energy model
  • Level set image segmentation method based on local guide core-fitting energy model

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Embodiment Construction

[0039] Concrete implementation steps of the present invention include as follows:

[0040] (1) Input the segmented image and set the initialization parameters: given scale parameter α, time step Δt, normalization parameter ε of Heavide function, symbolic distance function constant ρ, and covariance ξ;

[0041] (2) Initialize the level set function φ of the evolution curve, which is defined as the signed distance function φ(x,t)=0.

[0042] (3) calculate according to the curve evolution equation described in description step 4;

[0043] (4) Calculate the evolved level set function φ according to the Gaussian filter equation in step 5, that is, φ n =G ξ *φ n ;

[0044] (5) Judging whether the described level set evolution curve is satisfied and terminated, if yes, then output the images and segmentation results of each segmented region. Otherwise, the Gaussian filtered level set function φ n+1 = φ n As the initial level set function for the next iteration, go to step three....

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Abstract

The invention discloses a level set image segmentation method based on a local guide core-fitting energy model, and the method mainly comprises the steps: the definition of a level set function, the construction of a segmentation model energy functional, the simplification of an energy functional model, the evolution of the level set function, and the smoothing of the level set function. The method is used for extracting local information of an image based on local guide core-fitting energy functional, and Gaussian filtering is carried out in each iterative process, so as to avoid the periodic initialization of the level set function. The method not only improves the segmentation precision of a weak boundary target in a scene with nonuniform gray scale, but also completely avoids a problem of periodic initialization, and also reduces the computation complexity of an algorithm.

Description

technical field [0001] The present invention relates to an image segmentation method in the technical field of image processing, in particular to a local kernel-induced fitting (Local Kernel-induced Fitting, LKF) energy model level set image segmentation method. technical background [0002] The image segmentation method based on the variational level set (Variational Level Set Method) is widely used in the field of image processing, such as image segmentation, target extraction, and target tracking, due to its free topology and multi-information fusion. In the imaging process, due to the inherent defects of imaging equipment and the influence of factors such as uneven illumination, there is a wide range of gray distribution inhomogeneity in the actual image. In order to be able to segment images with inhomogeneous gray levels, Vese and Chan proposed a Piecewise Smooth (PS) model to solve the problem that the Piecewise Constant (PC) model could not segment images with inhomo...

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Application Information

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IPC IPC(8): G06T7/00
CPCG06T7/11
Inventor 方江雄刘花香刘军曾正军饶利民
Owner EAST CHINA UNIV OF TECH