access icon free Hybrid CBIR method using statistical, DWT-Entropy and POPMV-based feature sets

© The Institution of Engineering and Technology
Received 02/07/2018, Accepted 01/07/2019, Revised 18/05/2019, Published 09/07/2019

Content-based image retrieval (CBIR) is an image retrieval technique that can retrieve images by matching its feature set values. This research focuses on a novel CBIR method namely hybrid CBIR method using statistical, Discrete Wavelet Transform (DWT)-Entropy and Peak-oriented Octal Pattern-derived Majority Voting (POPMV)-based feature sets (CBIR_SWPOPMV) to efficiently extract the relevant colour images from the colour image dataset. The doctrine of the proposed method is influenced by a novel texture descriptor namely POPMV which is an octal pattern based on the histogram peak information, to bring about a majority voting-based feature set and three histogram-based feature sets. Furthermore, to improve the retrieval accuracy, the DWT-based Entropy feature set and the statistical feature set are also included. Finally, the Euclidean distance-based matching process brings more favourable relevant images with respect to the query image. The proposed methodology is experimentally compared with the existing recent CBIR versions by using seven standard databases such as Corel-1k, USPTex, MIT-VisTex, KTH-TIPS, KTH-TIPS2a, KTH-TIPS2a, Colored Brodatz and a user-contributed database named DB_VEG.

Inspec keywords: image texture; entropy; statistical analysis; discrete wavelet transforms; feature extraction; image retrieval; image matching

Other keywords: Colored Brodatz databases; USPTex databases; Euclidean distance-based matching process; histogram peak information; POPMV-based feature sets; texture descriptor; KTH-TIPS2a databases; hybrid CBIR_SWPOPMV method; query imaging; histogram-based feature sets; DB_VEG user-contributed database; MIT-VisTex databases; Corel-1k databases; KTH-TIPS databases; colour image dataset; content-based image retrieval technique; DWT-based entropy; peak-oriented octal pattern-derived majority voting; statistical feature set analysis; discrete wavelet transform-entropy; image matching

Subjects: Integral transforms; Computer vision and image processing techniques; Other topics in statistics; Image recognition; Other topics in statistics; Integral transforms

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