Phase congruency and ODBTC based image retrieval. Issue 10 (1st July 2020)

• Record Type: Journal Article
• Authors: Gupta, Shraddha; Modem, Sudhakar; Thakre, Vandana Vikas
• Is Part Of: IET image processing. Volume 14:Issue 10(2020)
• Page Start: 2195
• Page End: 2203
• Publication Date: 2020-07-01
• Subjects: feature extraction -- image coding -- image retrieval -- content‐based retrieval -- block codes; phase congruency feature -- ODBTC based image retrieval -- content based image retrieval -- ordered‐dither block truncation coding -- PCF -- feature extraction -- image brightness -- ODBTC features -- visual data processing domains -- edge detection -- corner detection -- storage space reduction -- performance metrics -- CBIR system -- image contrast -- temperature 1.0 K -- temperature 10.0 K; Image processing -- Periodicals; 621.36705
• DOI: 10.1049/iet-ipr.2019.1023
• Languages: English
• ISSNs: 1751-9659

Abstract

Abstract : In this study, the authors investigate content based image retrieval (CBIR) using ordered‐dither block truncation coding (ODBTC) and phase congruency feature (PCF). Relevant feature extraction plays a vital role for retrieving the image in CBIR. The unique reason to choose PCF with ODBTC is that it detects the edges and corners during variation of image while preserving image brightness and contrast. Combining the PCF and ODBTC features improves CBIR system usage in various visual data processing domains. Thus, yields a better CBIR system which assists in the reduction of storage space, decreases retrieval time and increases accuracy of the system. The precision and recall are used as performance metrics to evaluate the proposed method based on retrieval of relevant images. Extensive experimental results with Corel 1 K (1000 images), Corel 10 K (10000 images) and CALTECH 256 (30144 images) proves that the proposed method is more desirable than antecedent proposed CBIR system in terms of accuracy, precision and recall.