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All Journal Bulletin of Electrical Engineering and Informatics
Ayad I. Abdulsada
University of Basrah
Electrical & Electronics Engineering

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SMPP-CBIR: shorted and mixed aggregated image features for privacy-preserving content-based image retrieval Ali Lazim Lafta; Ayad I. Abdulsada
Bulletin of Electrical Engineering and Informatics Vol 11, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i5.4323

Abstract

Thanks to recent breakthroughs in photographic and digital technology, enormous amounts of image data are generated daily. Many content-based image retrieval (CBIR) systems have been developed for searching image collections. However, these systems need more computer and storage resources that can be met by cloud servers, since they supply a lot of processing power at a reasonable price. The protection of users' personal information is a worry for image owners since cloud services are not exactly trustworthy. In this paper, we suggest and put into practice a CBIR (SMPP-CBIR) technique for searching and retrieving ciphertext information that protects security. Asymmetric scalar-product-preserving encryption process (ASPE) is used to preserve aggregated mixed feature vectors while still enabling computation between them to describe the related picture collection. The k-means clustering algorithm is used to recursively arrange all encrypted attributes into a tree index in order to speed up search times. The findings show that SMPP-CBIR is more scalable, more precise, and faster in indexing and retrieval than earlier systems.
Co-Authors Ali Lazim Lafta