Human-centric Computing and Information Sciences · 2014 · 49 citations · 26 references
EngineeringImage RetrievalBiometricsImage SearchText MiningImage AnalysisInformation RetrievalData SciencePattern RecognitionContent AnalysisMachine VisionText IndexingImage SimilarityComputer VisionRemote SensingTexture AnalysisSearch Engine IndexingNovel Evaluationary ApproachIndexing TechniqueDirectional Binary PatternQuinary ValueContent-based Image RetrievalMultimedia Search
Abstract This paper presents a novel evaluationary approach to extract color-texture features for image retrieval application namely Color Directional Local Quinary Pattern (CDLQP). The proposed descriptor extracts the individual R, G and B channel wise directional edge information between reference pixel and its surrounding neighborhoods by computing its grey-level difference based on quinary value (−2, −1, 0, 1, 2) instead of binary and ternary value in 0°, 45°, 90°, and 135° directions of an image which are not present in literature (LBP, LTP, CS-LBP, LTrPs, DExPs, etc.). To evaluate the retrieval performance of the proposed descriptor, two experiments have been conducted on Core-5000 and MIT-Color databases respectively. The retrieval performances of the proposed descriptor show a significant improvement as compared with standard local binary pattern LBP, center-symmetric local binary pattern (CS-LBP), Directional binary pattern (DBC) and other existing transform domain techniques in IR system.
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A survey of content-based image retrieval with high-level semantics
Ying Liu, Dengsheng Zhang, Guojun Lu et al. · Pattern Recognition · 2006 · 1.7K citations