[1]WU Qiping,WU Chengmao.A fast and robust clustering segmentation algorithm for kernel space graphics[J].CAAI Transactions on Intelligent Systems,2019,14(4):804-811.[doi:10.11992/tis.201806045]
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A fast and robust clustering segmentation algorithm for kernel space graphics

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 14 Number of periods: 2019 4 Page number: 804-811 Column: 学术论文—机器学习 Public date: 2019-07-02
Title:
A fast and robust clustering segmentation algorithm for kernel space graphics
Author(s):
WU Qiping;  WU Chengmao
School of Electronic Engineering, Xi’an University of Posts and Telecommunications, Xi’an 710121, China
Keywords:
image segmentation; graph fuzzy clustering; kernel function; linear weighted image; neighborhood filtering; two-dimensional histogram; clustering validity; robustness
CLC:
TP391.41
DOI:
10.11992/tis.201806045
Abstract:
Addressing the existing problem of difficulty in realizing fast segmentation of large-scale images under strong noise interference, a fast robust kernel space graph fuzzy clustering segmentation algorithm is proposed. This algorithm first mapped the samples in European Space to the high dimensional feature space through the kernel function; subsequently, it constructed the linear weighted filtering image using the gray scale and spatial information of the pixel neighborhood in the image to be segmented and carried out the robust kernel space pattern fuzzy clustering on the image. The fast iterative expression of robust kernel space graph fuzzy clustering was obtained by introducing the two-dimensional histogram information corresponding to the mean value of the current clustering pixel and its neighboring pixels. Experimental test results of large size images interrupted by Gaussian and salt-and-pepper noise show that the segmentation, robustness, and real-time performance of the proposed segmentation algorithm have improved more significantly than those of the picture-based fuzzy clustering, and other fuzzy clustering segmentation algorithms.
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