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The variation between low-level and high-level features is identified as a semantic gap. The semantic gap is the biggest problem in CBIR. The visual characteristics are extracted from low-level features such as color, texture and shape. The low-level feature increases CBIRs performance level. The paper mainly focuses on an image retrieval system called combined color (TriCLR) (RGB, YCbCr, and [Formula: see text]) with the histogram of texture features in LBP (HistLBP), which, is known as a hybrid of three colors (TriCLR) with Histogram of LBP (TriCLR and HistLBP). The study also discusses the hybrid method in light of low-level features. Finally, the hybrid approach uses the (TriCLR and HistLBP) algorithm, which provides a new solution to the CBIR system that is better than the existing methods. <\/jats:p>","DOI":"10.1142\/s0219467825500214","type":"journal-article","created":{"date-parts":[[2023,9,27]],"date-time":"2023-09-27T04:21:43Z","timestamp":1695788503000},"source":"Crossref","is-referenced-by-count":2,"title":["Content-Based Image Retrieval (CBIR): Using Combined Color and Texture Features (TriCLR and HistLBP)"],"prefix":"10.1142","volume":"25","author":[{"given":"P. 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