Study of the similarity function in Indexing-First-One hashing

Y.-L. Lai; Z. Jin; B.-M. Goi; T.-Y. Chai

doi:10.1117/12.2280238

19 June 2017 Study of the similarity function in Indexing-First-One hashing

Y.-L. Lai, Z. Jin, B.-M. Goi, T.-Y. Chai

Proceedings Volume 10443, Second International Workshop on Pattern Recognition; 104431N (2017) https://doi.org/10.1117/12.2280238
Event: Second International Workshop on Pattern Recognition, 2017, Singapore, Singapore

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.

Citation Download Citation

Y.-L. Lai, Z. Jin, B.-M. Goi, and T.-Y. Chai "Study of the similarity function in Indexing-First-One hashing", Proc. SPIE 10443, Second International Workshop on Pattern Recognition, 104431N (19 June 2017); https://doi.org/10.1117/12.2280238

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available