19 June 2017 Study of the similarity function in Indexing-First-One hashing
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Proceedings Volume 10443, Second International Workshop on Pattern Recognition; 104431N (2017); doi: 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.
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Y.-L. Lai, Z. Jin, B.-M. Goi, 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); doi: 10.1117/12.2280238; http://dx.doi.org/10.1117/12.2280238
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KEYWORDS
Binary data

Iris recognition

Databases

Eye

Current controlled current source

Information technology

Pattern recognition

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