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.
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Kaushik, V.D., Gupta, A.K., Jayaraman, U., Gupta, P. (2012). Modified Geometric Hashing for Face Database Indexing. In: Huang, DS., Gan, Y., Gupta, P., Gromiha, M.M. (eds) Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence. ICIC 2011. Lecture Notes in Computer Science(), vol 6839. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25944-9_79
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DOI: https://doi.org/10.1007/978-3-642-25944-9_79
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-25943-2
Online ISBN: 978-3-642-25944-9
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