Computer Informatization and Mechanical System
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2020 Vol.3 Jun. No.3
Title: Multimedia image mining method based on fuzzy pixels difference iterative clustering Name: Ji-sheng Zhao Company: Department of Computer Science and Technology, Jiangsu food & ph Abstract: The traditional multimedia image mining based on association rules, has a big flaw in mining time, a multimedia image mining method based on fuzzy pixel difference iterative clustering is proposed, multimedia image index characteristic value is converted into relative membership degree for fuzzy concept index. On the basis of the multimedia image samples and fuzzy pixel difference comprehensive tradeoff metric equation of different types, the Lagrange function is constructed to acquire fuzzy pixel difference iterative clustering loop iteration model, the model is adopted to analyze average divergence inside cluster and average separation degree between clusters and choose the optimal clustering number value, so as to achieve mining of multimedia image. The results of simulation experiment shows that the mining time and energy consumption of the proposed method are better than the traditional method, and has a high value of application. Keyword: fuzzy pixels, difference iterative clustering, multimedia image, mining DOI: 10.12250/jpciams2020030111 Citation form: Ji-sheng Zhao.Multimedia image mining method based on fuzzy pixels difference iterative clus[J]. Computer Informatization and Mechanical System, 2020, vol. 3, pp. 114-119.

2020 Vol.3 Jun. No.3

Title: Multimedia image mining method based on fuzzy pixels difference iterative clustering
Name: Ji-sheng Zhao
Company: Department of Computer Science and Technology, Jiangsu food & ph
Abstract:
The traditional multimedia image mining based on association rules, has a big flaw in mining time, a multimedia image mining method based on fuzzy pixel difference iterative clustering is proposed, multimedia image index characteristic value is converted into relative membership degree for fuzzy concept index. On the basis of the multimedia image samples and fuzzy pixel difference comprehensive tradeoff metric equation of different types, the Lagrange function is constructed to acquire fuzzy pixel difference iterative clustering loop iteration model, the model is adopted to analyze average divergence inside cluster and average separation degree between clusters and choose the optimal clustering number value, so as to achieve mining of multimedia image. The results of simulation experiment shows that the mining time and energy consumption of the proposed method are better than the traditional method, and has a high value of application.
Keyword: fuzzy pixels, difference iterative clustering, multimedia image, mining
DOI: 10.12250/jpciams2020030111
Citation form: Ji-sheng Zhao.Multimedia image mining method based on fuzzy pixels difference iterative clus[J]. Computer Informatization and Mechanical System, 2020, vol. 3, pp. 114-119.

Reference:

[1] Zhong Chongfeng, Liu Zhi. An Improved Image Segmentation Algorithm Based on Genetic Fuzzy C-Means Clustering [J]. Journal of Changchun University of Science and Technology: Natural Science, 2014, (2): 62-67.
[2] Zhang Hong, Wu Fei, Zhang Xiaolong. Multimedia Data Clustering Based on Correlation Matrix Fusion [J]. Chinese Journal of Computers, 2011, 34 (9): 1705-1711.
[3] Cui Zhaohua, Gao Liqun, Ouyang Haibin. Improved fuzzy C-means clustering combined with the global best harmony search algorithm for image segmentation [J]. Journal of Image and Graphics, 2013, 18 (9): 1133-1141.
[4] Lu Binbin, Jia Zhenhong, Yang Jie. A new Fuzzy C

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