Monogenic scale space based region covariance matrix descriptor: An efficient and accurate face recognition algorithm

M. Sharmila Kumari, B. H. Shekar, N. Harivinod, K. Raghurama Holla

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we present a new face recognition algorithm based on region covariance matrix (RCM) descriptor computed in monogenic scale space. In the proposed model, local energy information and local phase information obtained using monogenic filter is used to represent a pixel at different scales to form region covariance matrix descriptor for each face image during training phase. An eigen-value based distance measure is used to compute the similarity between face images. Extensive experimentation on AT & T and YALE face database has been conducted to reveal the performance of the monogenic scale space based region covariance matrix method and comparative analysis is made with the basic RCM method and Gabor Wavelet based region covariance matrix method to exhibit the superiority of the proposed technique.

Original languageEnglish
Title of host publicationProceedings of the 2012 International Conference on Advances in Computing, Communications and Informatics, ICACCI'12
Pages717-720
Number of pages4
DOIs
Publication statusPublished - 17-09-2012
Event2012 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2012 - Chennai, India
Duration: 03-08-201205-08-2012

Publication series

NameACM International Conference Proceeding Series

Conference

Conference2012 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2012
Country/TerritoryIndia
CityChennai
Period03-08-1205-08-12

All Science Journal Classification (ASJC) codes

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

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