SMPP-CBIR: shorted and mixed aggregated image features for privacy-preserving content-based image retrieval
نویسندگان
چکیده
Thanks to recent breakthroughs in photographic and digital technology, enormous amounts of image data are generated daily. Many content-based retrieval (CBIR) systems have been developed for searching collections. However, these need more computer storage resources that can be met by cloud servers, since they supply a lot processing power at reasonable price. The protection users' personal information is worry owners services not exactly trustworthy. In this paper, we suggest put into practice CBIR (SMPP-CBIR) technique retrieving ciphertext protects security. Asymmetric scalar-product-preserving encryption process (ASPE) used preserve aggregated mixed feature vectors while still enabling computation between them describe the related picture collection. k-means clustering algorithm recursively arrange all encrypted attributes tree index order speed up search times. findings show SMPP-CBIR scalable, precise, faster indexing than earlier systems.
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ژورنال
عنوان ژورنال: Bulletin of Electrical Engineering and Informatics
سال: 2022
ISSN: ['2302-9285']
DOI: https://doi.org/10.11591/eei.v11i5.4323