Multimedia Tools and Applications

, Volume 76, Issue 18, pp 18731–18747 | Cite as

A biologically inspired spatio-chromatic feature for color object recognition

  • Tian Tian
  • Yun Zhang
  • Kim-Kwang Raymond Choo
  • Weijing SongEmail author


Color information has been acknowledged for its important role in object recognition and scene classification. How to describe the color characteristics and extract combined spatial and chromatic feature is a challenging task in computer vision. In this paper we extend the robust SIFT feature on processed opponent color channels to obtain a spatio-chromatic descriptor for color object recognition. The color information processing is implemented under a biologically inspired hierarchical framework, where cone cells, single-opponent and double-opponent cells are simulated respectively to mimic the color perception of primate visual system. The biologically inspired method is tested for object recognition task on two public datasets, and the results support the potential of our proposed approach.


Local image feature Color Scale invariant feature transform (SIFT) Object recognition 



This work is supported by the Fundamental Research Funds for the Central Universities, China University of Geosciences (Wuhan), the Provincial Natural Science Foundation of Hubei under Grant 2016CFB278, and the National Natural Science Foundation of China under Grant 61601416.


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Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  • Tian Tian
    • 1
  • Yun Zhang
    • 2
  • Kim-Kwang Raymond Choo
    • 3
  • Weijing Song
    • 1
    Email author
  1. 1.Hubei Key Laboratory of Intelligent Geo-Information Processing, College of Computer ScienceChina University of GeosciencesWuhanChina
  2. 2.Department of Information, Systems and Cyber SecurityUniversity of Texas at San AntonioSan AntonioUSA
  3. 3.Beijing Electro-Mechanical Engineering InstituteBeijingChina

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