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Image segmentation method based on distance potential field and self-adaptive balloon force

An image segmentation and balloon force technology, applied in image analysis, image data processing, instruments, etc., can solve the problems that the force field cannot be combined with the balloon force, cannot be changed, and the boundary leaks.

Inactive Publication Date: 2015-04-15
HARBIN INST OF TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0010] Although the GVF model has a large capture range and can converge concave edges, there are still three problems: 1. The force field range of the GVF model cannot be controlled by parameters
3. The force field of the GVF model cannot be combined with the balloon force, and it is difficult to segment the long tubular edge
The main problem with the balloon force is that once the expansion or contraction direction of the force is set, it cannot be changed. When dividing a long tubular edge, it is easy to cause boundary leakage

Method used

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  • Image segmentation method based on distance potential field and self-adaptive balloon force
  • Image segmentation method based on distance potential field and self-adaptive balloon force
  • Image segmentation method based on distance potential field and self-adaptive balloon force

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specific Embodiment approach 1

[0064] Specific Embodiment 1: This embodiment is based on the image segmentation method of the distance potential field and the adaptive balloon force, and uses the U-shaped graph with salt and pepper noise as the simulation data. The steps to realize the method are as follows:

[0065] 1. Construct the distance potential field operator; the construction method is:

[0066] a. Construct a square zero-valued matrix L with side length 2×R+1 R , construct a circular template with a radius of R in the matrix, and the selection of the radius R generally does not exceed half of the side length of the image to be processed;

[0067] Select R=30 in the present embodiment;

[0068] b. Set the value of the element (i, j) in the circular template to l(i, j), l(i, j) through the formula Obtained, where h and p are constants, generally 0.5≤h≤2, 1≤p≤3. The resulting square matrix L R is the distance potential field operator;

[0069] Select h=0.5, p=2 in this example;

[0070] 2. Use...

specific Embodiment approach 2

[0107] Specific implementation mode 2: This implementation mode is based on the image segmentation method of the distance potential field and the adaptive balloon force, and takes a real image containing a long tubular target as an example to describe in detail:

[0108] The steps to implement this method are as follows:

[0109] 1. Construct the distance potential field operator; the construction method is:

[0110] a. Construct a square zero-valued matrix L with side length 2×R+1 R , construct a circular template with a radius of R in the matrix, and the selection of the radius R generally does not exceed half of the side length of the image to be processed;

[0111] Select R=100 in the present embodiment;

[0112] b. Set the value of the element (i, j) in the circular template to l(i, j), l(i, j) through the formula Obtained, where h and p are constants, generally 0.5≤h≤2, 1≤p≤3. The resulting square matrix L R is the distance potential field operator;

[0113] Selec...

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Abstract

The invention discloses an image segmentation method based on a distance potential field and a self-adaptive balloon force, and belongs to the field of digital image processing. An objective of the present invention is to accurately split long tubular edges and to split an image with impulse noise. The method comprises the following steps: 1, constructing a distance potential field operator; 2, determining the distance potential field of the image using the constructed distance potential field, determining gradients of the potential field to obtain a distance force field, and normalizing the force field; 3, setting an initial contour, calculating the self-adaptive balloon force; 4, and plugging the distance force field calculated from image data and the self-adaptive balloon force into a mechanical equilibrium equation of the contour, using a finite difference method to solve the equation. The contour formed by steady-state solutions of the equation is a splitting result. The method is advantaged by relatively high noise-proof performance and being capable of splitting long tubular image objects.

Description

technical field [0001] The invention relates to an image segmentation method based on a Snake model, belonging to the field of digital image processing. Background technique [0002] Snake model, also known as active contour model, snake model. The meaning of the active contour is to manually or automatically set the initial contour around the target to be segmented, and to give the initial contour energy. The contour deforms under the action of the topological internal force of the model itself and the external force generated by the grayscale data of the image, and moves like a snake. When the energy of the contour reaches the minimum, the position of the contour is the edge of the target to be segmented. [0003] The Snake model is the process of transforming the image segmentation problem into the minimization of the energy functional function. The outstanding advantage of the active contour is that once the initial contour is set, the subsequent contour evolution does...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T7/00
Inventor 刘宛予黄建平吴琦张延丽楚春雨
Owner HARBIN INST OF TECH
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