Active contour model image segmentation method based on local Gaussian distribution fitting and local signature energy driving

Abstract

The invention provides an active contour model image segmentation method based on local Gaussian distribution fitting and local signature energy driving, and belongs to the technical field of image processing. The active contour model image segmentation method based on local Gaussian distribution fitting and local signature energy driving includes the following steps: S1, inputting an original image I(x); S2, calculating the local entropy of the image so as to obtain a local signature energy item of the image; S3, initialization level function Phi=Phi0(x); S4, initialization coefficients: alpha, beta, lambda1, lambda2, Mu, Nu, epsilon, sigma and deltat; S5, calculating local fitting energy items e1 and e2; S6, update level set function Phi; and S7, determining whether the level set evolution curve can satisfy the convergence criterion, and if not, turning to the step S5 to continue calculation until the termination condition is satisfied. The active contour model image segmentation method based on local Gaussian distribution fitting and local signature energy driving can realize segmentation of the target having nonuniform gray scale, is not sensitive to the shape, the size and the position of the initial contour curve, and has certain noise immunity.

Description

technical field [0001] The invention belongs to the technical field of image processing, and relates to an active contour model image segmentation method, in particular to an active contour model image segmentation method based on local Gaussian distribution fitting and local sign difference energy drive. Background technique [0002] With the rapid development of computer science and technology, image segmentation, as a basic subject in the fields of image processing and computer vision, object tracking, and medical imaging, has high application and research value. In the past few decades, researchers have made great efforts to solve the problem of image segmentation, and proposed many segmentation algorithms, among which the active contour model has become one of the more active methods in this field. [0003] Active contour models expressed by curve evolution theory and level set method can generally be divided into two types: edge-based models and region-based models. T...

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Problems solved by technology

However, the LBF model is sensitive to image noise and initial contour curves, and the energy equation tends to fall into a local minimum

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