Visual Feature Clustering Method for Image Based on Cloud Computing Technology

Authors

  • Haifeng Shi School of Network and Communication, Nanjing Vocational College of Information Technology, Nanjing 210023, China
  • Ling Shang School of Network and Communication, Nanjing Vocational College of Information Technology, Nanjing 210023, China

Abstract

In order to significantly improve the performance of image classification, a visual feature clustering method for image based on cloud computing technology is proposed. The energy regression filtering algorithm is used to filter and denoise the image, the features of the denoised image are extracted from the global features and local features, and the mutation features and static features in the image are standardized. The multiple visual features integration of the image is achieved by means of multi-feature statistics, spectrum integration processing and structure integration. The K-means clustering algorithm is used to cluster the integrated image visual features. The parallel processing process in cloud computing technology is used to convert each iteration of the serial K-means algorithm into a Map Reduce calculation, to realize the image visual feature clustering. Experimental results show that this method can effectively achieve image denoising, has high feature integration and good clustering performance.

Keywords: cloud computing technology, image visual features, clustering algorithm, filtering algorithm, feature integration, parallelization.

Cite As

H. Shi, L. Shang, "Visual Feature Clustering Method for Image Based on Cloud Computing Technology", Engineering Intelligent Systems, vol. 31 no. 2, pp. 105-113, 2023.






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Published

2023-03-01

Issue

Vol. 31 No. 2 (2023): International Journal of Engineering Intelligent Systems

Section

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