New colour SIFT descriptors for image classification with applications to biometrics

Abhishek Verma, Chengjun Liu, Jiancheng Jia

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

Abstract

This paper first presents a new oRGB-SIFT descriptor, and then integrates it with other colour SIFT features to produce the novel Colour SIFT Fusion (CSF) and the Colour Greyscale SIFT Fusion (CGSF) descriptors for image classification with special applications to biometrics. Classification is implemented using a novel EFM-KNN classifier, which combines the Enhanced Fisher Model (EFM) and the K Nearest Neighbour (KNN) decision rule. The effectiveness of the proposed descriptors and classification method are evaluated using 20 image categories from two large scale, grand challenge datasets: the Caltech 256 database and the UPOL Iris database.

Original languageEnglish (US)
Pages (from-to)56-75
Number of pages20
JournalInternational Journal of Biometrics
Volume3
Issue number1
DOIs
StatePublished - 2011

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition
  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Applied Mathematics

Keywords

  • Biometrics
  • CGSF
  • CSF
  • Colour SIFT fusion
  • Colour greyscale SIFT fusion
  • EFM-KNN classifier
  • Image classification
  • ORGB-SIFT descriptor

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