Title: CBIR using content frequency and colour features

Authors: Youness Chawki; Khalid El Asnaoui; Mohammed Ouanan; Brahim Aksasse

Addresses: M2I Laboratory, Department of Computer Science, Faculty of Science and Techniques, Moulay Ismail University, BP 509 Boutalamine Errachidia, Morocco ' M2I Laboratory, Department of Computer Science, Faculty of Science and Techniques, Moulay Ismail University, BP 509 Boutalamine Errachidia, Morocco ' M2I Laboratory, Department of Computer Science, Faculty of Science and Techniques, Moulay Ismail University, BP 509 Boutalamine Errachidia, Morocco ' M2I Laboratory, Department of Computer Science, Faculty of Science and Techniques, Moulay Ismail University, BP 509 Boutalamine Errachidia, Morocco

Abstract: Due to the diversity of the image content, we propose in this study a new technique for content-based image retrieval (CBIR) to characterise the image. In this scenario, all images are characterised by their frequency content and their colour information. Indeed, using the high resolution spectral analysis methods, especially the 2D estimation of signal parameters via rotational invariance techniques (ESPRIT) we extract from the image its content frequency and with statistical moment its colour information in order to construct a new vector descriptor. The experimental results applied to the coil-100 database show the robustness of our approach, the precision average can be reaches 90.57%.

Keywords: content-based image retrieval; CBIR; frequency content; high resolution; spectral analysis; 2D ESPRIT; colour feature; statistical moments.

DOI: 10.1504/IJIM.2021.115754

International Journal of Image Mining, 2021 Vol.4 No.1, pp.24 - 35

Accepted: 07 Jul 2020
Published online: 21 Jun 2021 *

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