A biologically inspired spatio-chromatic feature for color object recognition

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 pro...

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Bibliographic Details
Published in:Multimedia tools and applications 2017-09, Vol.76 (18), p.18731-18747
Main Authors: Tian, Tian, Zhang, Yun, Choo, Kim-Kwang Raymond, Song, Weijing
Format: Article
Language:English
Subjects:
Color vision
Computer Communication Networks
Computer Science
Computer simulation
Computer vision
Data processing
Data Structures and Information Theory
Feature extraction
Feature recognition
Information processing
Multimedia Information Systems
Object recognition
Simulation
Special Purpose and Application-Based Systems
Visual perception
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Summary: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.
ISSN:1380-7501
1573-7721
DOI:10.1007/s11042-016-4252-y