Energy conservation by adaptive feature loading for mobile content-based image retrieval
Proceedings of the 13th international symposium on Low power electronics and design
Simulated evaluation of faceted browsing based on feature selection
Multimedia Tools and Applications
Energy Conservation for Image Retrieval on Mobile Systems
ACM Transactions on Embedded Computing Systems (TECS)
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Content-based image retrieval (CBIR) systems with user relevance feedback are considered. The influence of the type and the number of feature vector (FV) components on the retrieval efficiency was investigated. We compared a CBIR system with a very small number of FV components (only 25 components describing color and texture) with a system with a high-dimensional FV inspired by MPEG-7 (556 coordinates describing color, texture and line directions), as well as with a system using feature vector reduction (FVR) of about 90% (with about 50 FV components from the full-length 556-component FVs). The systems are tested over the annotated Corel 1K and Corel 60K datasets. Simulation results show that a decreased number of FV components does not have significant influence on the quality of image retrieval, while the processing time is reduced compared to CBIR with full-length FV and/or FVR.