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Narrowband constraint-based local segmentation method for geometric activity contour model image

A geometric active contour and local segmentation technology, applied in the field of image processing, can solve the problems of unstable narrow-band control, insufficient precision of curve evolution, and accurate segmentation of images with uneven gray levels, so as to promote correct and efficient evolution and improve stability , Improve the effect of evolutionary accuracy and efficiency

Inactive Publication Date: 2018-05-04
SHANDONG UNIV
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Problems solved by technology

[0003] The present invention aims at the problems of unstable narrow-band control and insufficient precision of curve evolution existing in local segmentation of uneven gray scale images, and the energy function model fitted only with global energy items and local energy items cannot quickly and accurately segment uneven gray scales image problem, a local segmentation method based on narrow-band constraint geometric active contour model gray level uneven image is proposed

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  • Narrowband constraint-based local segmentation method for geometric activity contour model image
  • Narrowband constraint-based local segmentation method for geometric activity contour model image
  • Narrowband constraint-based local segmentation method for geometric activity contour model image

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[0019] The present invention will be described in further detail below in conjunction with the accompanying drawings and specific embodiments. Figure 4 For the flow chart of the local segmentation method of the geometric active contour model based on narrow-band constraints in the present invention, reference will be made to figure 1 , figure 2 and image 3 illustrate Figure 4 processing steps.

[0020] Step 1: Read in the target image I, and perform denoising processing on the image, such as figure 1 as shown in (a);

[0021] Step 2: Obtain the rough segmentation result according to the particle swarm threshold segmentation method;

[0022] (1) Randomly generate 20 particles in the gray space of image I, set the initial position and initial flight speed of these particles, and the parameter a in formulas (4) and (5) 1 and a 2 , where a 1 is the contribution proportion coefficient of the individual optimal position to the speed update, a 2 is the contribution propo...

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Abstract

The invention discloses a narrowband constraint-based local segmentation method for a geometric activity contour model and belongs to the field of image processing. The method comprises the followingsteps of constructing a narrow-band range based on particle swarm threshold segmentation and morphology expansion; constructing an energy function of fusing a global energy item and a local energy item by a self-adaptive coefficient; and solving the energy function by adopting the level set method. According to the invention, the local segmentation calculation region is optimized, and the self-adaptation coefficient of the global energy term and the local energy term is achieved. Therefore, the efficiency and the accuracy of the local segmentation of a grayscale uneven image are improved. Theproblems that the narrow-band control is unstable and the curve evolution precision is insufficient during the local segmentation of the grayscale uneven image are solved. The problem that the energyfunction model fitted by the global energy item and the local energy item cannot be rapidly and accurately segmented is also solved.

Description

technical field [0001] The invention belongs to the field of image processing, in particular to an image segmentation method based on an active contour model and a level set. Background technique [0002] Image segmentation is an image processing method that divides an image into areas with different properties and characteristics. It is widely used in medical image processing, remote sensing image processing, etc. For various application requirements, researchers have proposed many image segmentation methods. Among them, the active contour model (Active Contour Model, ACM) has attracted many scholars because of its strong mathematical theoretical foundation and efficient numerical scheme based on the level set function (Level Set Function, LSF). Active contour models are mainly divided into two categories: active contour models based on edge information and active contour models based on region information. The active contour model based on edge information uses the image...

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Application Information

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IPC IPC(8): G06T7/11G06T7/136G06T7/155G06T5/00G06T5/30
CPCG06T5/30G06T7/11G06T7/136G06T7/155G06T2207/20036G06T5/70
Inventor 董恩清刘肖孙文燕薛鹏纪慧中熊文硕
Owner SHANDONG UNIV
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