Human face identification using invariant descriptions and a genetic algorithm

R. Pinto-Elías, J. H. Sossa-Azuela

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

1 Scopus citations

Abstract

© Springer-Verlag Berlin Heidelberg 1998. A new method to automatically identify a human face onto a 2D gray level image is presented. The method uses an invariant description of the face and a genetic algorithm to accomplish the task. The features used are the first four translation, rotation and scale moment invariants proposed by Hu [1]. In a first step, an image possibly containing a face is first divided into small cells of fixed size of 5 × 5 pixels. For each cell, the ordinary moments are next computed. From these, the corresponding Hu’s invariants are then derived. Human face identification is thus accomplished by grouping individual cells using a genetic algorithm by fitting a specific cost function. This cost function corresponds to the invariant description of a human face given in terms of the detected image features.
Original languageAmerican English
Title of host publicationHuman face identification using invariant descriptions and a genetic algorithm
Pages293-302
Number of pages262
ISBN (Electronic)3540649921, 9783540649922
StatePublished - 1 Jan 1998
EventLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) -
Duration: 1 Jan 2014 → …

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume1484
ISSN (Print)0302-9743

Conference

ConferenceLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Period1/01/14 → …

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Pinto-Elías, R., & Sossa-Azuela, J. H. (1998). Human face identification using invariant descriptions and a genetic algorithm. In Human face identification using invariant descriptions and a genetic algorithm (pp. 293-302). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1484).