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A content-based image retrieval system based on Color Ton Distribution descriptors

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Abstract

In this paper, we have proposed a content-based image retrieval (CBIR) system based on two kinds of features: intra-class and inter-class. Intra-class features are a new layout for color distribution of an image in RGB color space. This layout has been proposed based on the concept of co-occurrence matrix and called Distribution of Color Ton. Inter-class features are extracted using dual-tree complex wavelet transform, singular value decomposition (SVD), and conceptual segmentation based on human vision system. In the proposed method, these two kinds of features together are followed by self-organizing map as classifier to have an efficient CBIR system which considers both structural and signal processing feature descriptors advantages. The proposed approach tested by using Corel and VisTex image data sets and the results were satisfactory. The experimental results showed that the proposed method had better performance versus the other related ones.

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Authors and Affiliations

  1. Department of Electrical and Computer Engineering, Shahid Beheshti University G.C., Tehran, Iran

    Mostafa Rahimi & Mohsen Ebrahimi Moghaddam

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  1. Mostafa Rahimi
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  2. Mohsen Ebrahimi Moghaddam
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Correspondence to Mohsen Ebrahimi Moghaddam.

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Rahimi, M., Ebrahimi Moghaddam, M. A content-based image retrieval system based on Color Ton Distribution descriptors. SIViP 9, 691–704 (2015). https://doi.org/10.1007/s11760-013-0506-6

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