High-definition image automatic segmentation method based on continued fraction level set

A high-definition image and automatic segmentation technology, applied in the field of image processing, can solve the problems of insufficient target details and slow convergence, so as to improve the convergence speed and accuracy, good recursion and extrapolation, and solve the problem of large amount of calculation Effect

Inactive Publication Date: 2013-05-29
SUN YAT SEN UNIV
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Problems solved by technology

[0005] The purpose of the present invention is to provide an automatic segmentation method for high-definition images, which can solve the problems of slow convergence and insufficient target details in current level set image segmentation methods, and the accuracy of segmentation is better guaranteed

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  • High-definition image automatic segmentation method based on continued fraction level set
  • High-definition image automatic segmentation method based on continued fraction level set
  • High-definition image automatic segmentation method based on continued fraction level set

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[0026] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

[0027] refer to figure 1 , the high-definition image automatic segmentation method based on the continued fraction level set of the technical solution comprises the following steps:

[0028] Step S001: Input the high-definition image to be segmented, and use the scattered grid to represent the discretized level set function;

[0029] Step S002: For the discretized level set function, use a recursive method to evolve the level set of the corresponding node in each ...

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Abstract

The invention discloses a high-definition image automatic segmentation method based on continued fraction level set. The method includes steps of 1, inputting a high-definition image to be segmented, and using a decentralized grid to indicate a discretization level set function; 2, evolving a corresponding level set of each node in the discretization level set function by using a recurrence method; 3, updating the level set function; 4, judging a zero level set of the updated level set function; 5, performing 'and' operation on all zero level sets to obtain a closure activity contour line. The method can not only automatically finish high-definition image segmentation in real time and steadily, but also effectively improve a detail ability of depicting segmentation targets by using continued fraction level sets to segment high-definition images.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to a high-definition image segmentation method based on a continued fraction level set. Background technique [0002] Image segmentation occupies an important position in image engineering. It is a key step in image processing and image analysis. Since its inception in the 1970s, there have been many algorithms based on different theories (such as neural networks, fuzzy theory, and swarm intelligence algorithms). image segmentation method. In 1987, Kass and others proposed the theory of active contour model and applied the parameter active contour model to image segmentation. It expresses the curve in the form of explicit parameterization, and generally uses the partial differential equation of curve evolution to approximate the target. The realization method is to use Lagrange coordinates to express explicitly, but its disadvantage is that the curve evolution equation is ...

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Application Information

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IPC IPC(8): G06T7/00
Inventor 罗笑南邓伟财林格
Owner SUN YAT SEN UNIV
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