A Hybrid model for face recognition using facial components

Mehrtash T. Harandi, Majid Nili Ahmadabadi, Babak N. Araabi

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

3 Citations (Scopus)

Abstract

It is generally agreed that faces are not recognized only by utilizing some holistic search among all learned faces, but also through a feature analysis that aimed to specify more important features of each specific face. This paper addresses a novel decision strategy that efficiently uses both holistic and facial component (eye, nose and mouth) feature analysis to recognize faces. The proposed algorithm first performs a holistic search using the whole image features and selects probable candidates for further processing. Then the facial features of these probable candidates are compared and classified with the stored patterns in the train set. Finally the classification results are fused with a weighted majority voting to form the final decision. Simulation studies justify the superior performance of the proposed method as compared to that of Eigenface method.

Original languageEnglish
Title of host publication2007 9th International Symposium on Signal Processing and its Applications, ISSPA 2007, Proceedings
DOIs
Publication statusPublished - 1 Dec 2007
Externally publishedYes
Event2007 9th International Symposium on Signal Processing and its Applications, ISSPA 2007 - Sharjah, United Arab Emirates
Duration: 12 Feb 200715 Feb 2007

Publication series

Name2007 9th International Symposium on Signal Processing and its Applications, ISSPA 2007, Proceedings

Conference

Conference2007 9th International Symposium on Signal Processing and its Applications, ISSPA 2007
CountryUnited Arab Emirates
CitySharjah
Period12/02/0715/02/07

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