Image segmentation method based on multi-kernel local information FCM algorithm

A technology of image segmentation and local information, applied in image analysis, image data processing, calculation, etc., can solve the problems of FILCM algorithm pollution, etc., and achieve the effect of increasing resistance to variation and robustness, accurate image segmentation, and accurate clustering results

Inactive Publication Date: 2017-06-13
HEFEI UNIV OF TECH
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Problems solved by technology

[0007] In order to overcome the deficiencies in the prior art above, the present invention proposes an image segmentation method based on the multi-core local information FCM algorithm, in order to avoid the problem that FCM is sensitive to noise points and the FILCM algorithm is polluted in the neighborhood pixels, and at the same time It can find the most suitable weight value and return the size of the current membership value, thereby improving the reliability and convergence of the algorithm, thereby improving the accuracy of image segmentation

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  • Image segmentation method based on multi-kernel local information FCM algorithm
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Embodiment Construction

[0040] In this embodiment, an image segmentation method based on the multi-core local information FCM algorithm is performed according to the following steps:

[0041] Step 1. For an image with n pixels, let X={x 1 ,x 2 ,...,x j ,...,x n} represents the pixel set of the image, x j Indicates the jth pixel; 1≤j≤n, n is the number of pixels; optimally divide the pixel set X, so that the objective function value J shown in formula (1) is the smallest:

[0042]

[0043] In formula (1), i represents the i-th category, c represents the number of categories divided, and 1≤i≤c, u ij represents the jth pixel x j The membership degree value of the i-th class, and U={u ij | i＝1,2,…,c；j＝1,2,…,n} represents the membership matrix; 0≤u ij ≤1; Indicates that the j-th pixel belongs to the m-th power of the membership degree of the i-th class, and m is a weighted index, indicating the degree of clustering fuzziness; P ij is a balance factor, reflecting the spatial information from ...

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Abstract

The invention discloses an image segmentation method based on a multi-kernellocal information FCM algorithm. The image segmentation method is characterized by including the steps that 1, optimal division is carried out on a pixel set, so that the value of a target function is made minimum; 2, an initial membership grade matrix and an initialized clustering center are obtained; 3, a membership grade value and the clustering center are obtained through iteration; 4, a target function after a weight index is introduced is obtained. The image segmentation method can accurately avoid that an FCM is sensitive to noise points, and in implementation of a common kernel method, selection of a kernel function is not determined, meanwhile can find the most appropriate weight value and a current membership grade value to improve the reliability and astringency of the algorithm, is applied to image segmentation, and can achieve a good image segmentation effect.

Description

technical field [0001] The invention belongs to an algorithm for data classification in the field of data mining, in particular to a fuzzy c-means clustering algorithm of multi-core local information, which is applied to image segmentation. Background technique [0002] Clustering is a very important branch of unsupervised pattern recognition. The ultimate goal of clustering is to make the distance between similar pixels as small as possible and to make the distance between different pixels as large as possible. In this way, data can be distinguished. , categorical data. Image processing is an important part of computer vision. Fuzzy clustering is used to meet the needs of two aspects. First, the subjectivity of human vision makes images suitable for processing by fuzzy means. Second, the lack of training pixel images requires unsupervised The analysis of fuzzy clustering in the field of image processing is the most widely used image segmentation, which is equivalent to uns...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/10
Inventor 唐益明赵跟陆胡相慧任福继丰刚永
Owner HEFEI UNIV OF TECH
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