Modified geometric hashing for face database indexing

Authors:
Vandana Dixit Kaushik;Amit K. Gupta;Umarani Jayaraman;Phalguni Gupta
Affiliations:
Department of Computer Science & Engineering, Hartcourt Butler Technological Institute, Kanpur, India;Department of Computer Science & Engineering, Indian Institute of Technology Kanpur, Kanpur, India;Department of Computer Science & Engineering, Indian Institute of Technology Kanpur, Kanpur, India;Department of Computer Science & Engineering, Indian Institute of Technology Kanpur, Kanpur, India
Venue:
ICIC'11 Proceedings of the 7th international conference on Advanced Intelligent Computing Theories and Applications: with aspects of artificial intelligence
Year:
2011

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Abstract

This paper presents a modified geometric hashing technique to index the database of facial images. The technique makes use of minimum amount of search space and memory to provide best matches with high accuracy against a query image. Features are extracted using Speeded-Up Robust Features (SURF) operator. To make these features invariant to translation, rotation and scaling, a pre-processing technique consisting of mean centering, principal components, rotation and normalization has been proposed. The proposed geometric hashing is used to hash these features to index each facial image in the database. It has achieved more than 99% hit rate for top 4 best matches.