Chapter

Computer Vision – ECCV 2012

Volume 7576 of the series Lecture Notes in Computer Science pp 312-324

A New Biologically Inspired Color Image Descriptor

  • Jun ZhangAffiliated withDepartment of Cognitive Linguistic & Psychological Sciences, Institute for Brain Sciences, Brown UniversitySchool of Computer & Information, Hefei University of Technology
  • , Youssef BarhomiAffiliated withDepartment of Cognitive Linguistic & Psychological Sciences, Institute for Brain Sciences, Brown University
  • , Thomas SerreAffiliated withDepartment of Cognitive Linguistic & Psychological Sciences, Institute for Brain Sciences, Brown University

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Abstract

We describe a novel framework for the joint processing of color and shape information in natural images. A hierarchical non-linear spatio-chromatic operator yields spatial and chromatic opponent channels, which mimics processing in the primate visual cortex. We extend two popular object recognition systems (i.e., the Hmax hierarchical model of visual processing and a sift-based bag-of-words approach) to incorporate color information along with shape information. We further use the framework in combination with the gist algorithm for scene categorization as well as the Berkeley segmentation algorithm. In all cases, the proposed approach is shown to outperform standard grayscale/shape-based descriptors as well as alternative color processing schemes on several datasets.

Keywords

image descriptor color Hmax sift bag-of-words gist object recognition scene categorization segmentation