Method and system for constructing adaptive weight active contour model based on fractional differential information

An active contour model and fractional differentiation technology, applied in the field of image processing, can solve the problems of sensitive initial image contour and slow calculation

Active Publication Date: 2019-05-10
SHENZHEN UNIV
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AI Technical Summary

Problems solved by technology

[0034] Although the LRCV model can handle non-homogeneous images, it only considers the local information of the image and is sensitive to the initial contour of the image.
In addition, the amount of calculation is also slow

Method used

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  • Method and system for constructing adaptive weight active contour model based on fractional differential information
  • Method and system for constructing adaptive weight active contour model based on fractional differential information
  • Method and system for constructing adaptive weight active contour model based on fractional differential information

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Embodiment Construction

[0063] The invention discloses a method for constructing an adaptive weight active contour model based on fractional differential information. The specific technical scheme is:

[0064] 1. The proposed model:

[0065] The proposed model mainly includes two items, global items and local items. The global term still introduces the data fitting term of the CV model, namely:

[0066] E G (C,c 1 ,c 2 )=∫ in(C) |I-c 1 | 2 dx+∫ out(C) |I-c 2 | 2 dx, (12)

[0067] In the above formula, c 1 ,c 2 Is defined in equations (5) and (6).

[0068] For local terms, the following first introduces the fractional differentiation in the Fourier transform domain, and then introduces the fractional degree mode, then constructs the fractional difference image, and finally constructs a new local term.

[0069] For a given univariate function f(x), its Fourier transform is defined as follows:

[0070]

[0071] According to the properties of the Fourier transform differential, the nth-order differential in the F...

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Abstract

The invention provides an adaptive weight activity contour model construction method based on the fractional order differential information and a system. The system comprises an input module, an initiation module, a first calculation module, a second calculation module, a determination module and an output module. The system is advantaged in that fractional order differential is introduced, a new difference image is constructed, a local term is constructed by utilizing the difference image, and a new activity contour model is proposed; by utilizing the fractional order gradient mode information, one adaptive weight is proposed, so local and global terms of the model can be dynamically adjusted; by utilizing change of an inner area of an evolution curve, a new evolution stop standard is proposed, and the evolution curve can automatically stop at a correct boundary.

Description

Technical field [0001] The present invention relates to the field of image processing technology, in particular to a method and system for constructing an adaptive weight active contour model based on fractional differential information. Background technique [0002] Image segmentation is of great significance to computer vision, pattern recognition, medical image processing, etc., and active contour model is one of the important tools for image segmentation. The algorithm first initializes a closed curve in the image, and then moves the initial curve to the boundary of the target object by minimizing the energy functional to obtain the image segmentation result. [0003] According to the different ways of contour evolution, active contour models can be divided into boundary-based models and region-based models. The boundary-based model uses boundary information to attract the active contour to move toward the target boundary, while the region-based model uses specific region desc...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T7/181
CPCG06T2207/20004
Inventor 陈波张陈陈文胜潘彬彬周晓慧
Owner SHENZHEN UNIV
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