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Enhanced hybrid CBIR based on multichannel LBP oriented color descriptor and HSV color statistical feature

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Abstract

Internet applications stores vast quantity of images into databases of server and also several quantities of images are also retrieved from databases. This phenomenon projects the CBIR system as a vital need. The Content based Image Retrieval (CBIR) is an image retrieval system that is mostly demanded by the fields such as agriculture object recognition, biomedical, etc. The CBIR method that is imparted in this paper is Enhanced Hybrid CBIR based on Multichannel LBP oriented color descriptor and HSV color statistical feature(CBIR_MCLBP_HSV). This method employs the Hybrid feature sets which are generated by histogram oriented features and statistical features. The main contribution of this method is the new color-image-descriptor which is entitled as Multichannel LBP Oriented Color image descriptor (MCLBP). To strengthen this CBIR system, the HSV color space oriented statistical features such as Mean and Standard deviation are included in this new framework. The reduced feature sets from MCLP and the usage of HSV color space results in fast and higher retrieval rate. This excellent method is fit for large size online image retrieval. The proposed methodology is experimentally analyzed and compared with the existing recent CBIR algorithms with the help of three standard databases (DB_Corel1k, DB_USPTex and KTH-TIPS2a) and a user contributed database named DB_VEG.

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Authors and Affiliations

  1. Department of PG Computer Science, Nesamony Memorial Christian College, Marthandam, India

    D. Latha & C. Jaspin Jeba Sheela

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  1. D. Latha
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  2. C. Jaspin Jeba Sheela
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Correspondence to D. Latha.

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Latha, D., Sheela, C.J.J. Enhanced hybrid CBIR based on multichannel LBP oriented color descriptor and HSV color statistical feature. Multimed Tools Appl 81, 23801–23818 (2022). https://doi.org/10.1007/s11042-022-12568-x

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  • DOI: https://doi.org/10.1007/s11042-022-12568-x

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