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Proceedings Paper

Study of the similarity function in Indexing-First-One hashing
Author(s): Y.-L. Lai; Z. Jin; B.-M. Goi; T.-Y. Chai
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Paper Abstract

The recent proposed Indexing-First-One (IFO) hashing is a latest technique that is particularly adopted for eye iris template protection, i.e. IrisCode. However, IFO employs the measure of Jaccard Similarity (JS) initiated from Min-hashing has yet been adequately discussed. In this paper, we explore the nature of JS in binary domain and further propose a mathematical formulation to generalize the usage of JS, which is subsequently verified by using CASIA v3-Interval iris database. Our study reveals that JS applied in IFO hashing is a generalized version in measure two input objects with respect to Min-Hashing where the coefficient of JS is equal to one. With this understanding, IFO hashing can propagate the useful properties of Min-hashing, i.e. similarity preservation, thus favorable for similarity searching or recognition in binary space.

Paper Details

Date Published: 19 June 2017
PDF: 5 pages
Proc. SPIE 10443, Second International Workshop on Pattern Recognition, 104431N (19 June 2017); doi: 10.1117/12.2280238
Show Author Affiliations
Y.-L. Lai, Univ. Tunku Abdul Rahman (Malaysia)
Z. Jin, Monash Univ. Malaysia (Malaysia)
B.-M. Goi, Univ. Tunku Abdul Rahman (Malaysia)
T.-Y. Chai, Univ. Tunku Abdul Rahman (Malaysia)

Published in SPIE Proceedings Vol. 10443:
Second International Workshop on Pattern Recognition
Xudong Jiang; Masayuki Arai; Guojian Chen, Editor(s)

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