Content-Based Image Retrieval Using Multi-Resolution Multi-Direction Filtering-Based CLBP Texture Features and Color Autocorrelogram Features

  • Bu, Hee-Hyung (School of Computer Science and Engineering, Kyungpook National University) ;
  • Kim, Nam-Chul (School of Electronic Engineering, Kyungpook National University) ;
  • Yun, Byoung-Ju (School of Electronic Engineering, Kyungpook National University) ;
  • Kim, Sung-Ho (School of Computer Science and Engineering, Kyungpook National University)
  • Received : 2018.10.02
  • Accepted : 2019.03.08
  • Published : 2020.08.31


We propose a content-based image retrieval system that uses a combination of completed local binary pattern (CLBP) and color autocorrelogram. CLBP features are extracted on a multi-resolution multi-direction filtered domain of value component. Color autocorrelogram features are extracted in two dimensions of hue and saturation components. Experiment results revealed that the proposed method yields a lot of improvement when compared with the methods that use partial features employed in the proposed method. It is also superior to the conventional CLBP, the color autocorrelogram using R, G, and B components, and the multichannel decoded local binary pattern which is one of the latest methods.



This study was supported by the BK21 Plus project (SW Human Resource Development Program for Supporting Smart Life) funded by the Ministry of Education, School of Computer Science and Engineering, Kyungpook National University, Korea (No. 21A20131600005).


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