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Laser medical image processing based on neighborhood concerning Gaussian mixture model
Author(s): Yuting Lv
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Paper Abstract

The traditional Gaussian Mixture Model is sensitive to noise in laser medical image processing, and its segmentation accuracy is not high enough. In order to remedy these defects, the Neighborhood Concerning Gaussian Mixture Model is adopted. The gray value of the center pixel in every neighborhood block is updated by the information of the neighborhood pixels according to the close correlation between them. After remolded, the image is decomposed by double Gaussian Mixture Model, which further refines the decomposition of the mixture model and improves the accuracy and anti-noise performance of image segmentation. Finally, experiments are carried out to verify the feasibility of the method. The results of the experiments show that the method of image segmentation based on the Neighborhood Concerning Gaussian Mixture Model can significantly improve the noise suppression ability, and achieve a good segmentation effect with high efficiency, while retaining the image contour and details better.

Paper Details

Date Published: 17 May 2019
PDF: 8 pages
Proc. SPIE 11170, 14th National Conference on Laser Technology and Optoelectronics (LTO 2019), 111703K (17 May 2019); doi: 10.1117/12.2533924
Show Author Affiliations
Yuting Lv, Shanxi Univ. (China)


Published in SPIE Proceedings Vol. 11170:
14th National Conference on Laser Technology and Optoelectronics (LTO 2019)
Jianqiang Zhu; Weibiao Chen; Zhenxi Zhang; Minlin Zhong; Pu Wang; Jianrong Qiu, Editor(s)

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