Paper Info
Title
Iris code hashing
Abstract
This paper proposes an indexing technique for iris database using iris codes. Iris code which is the textural features of an iris is efficiently hashed such that it reduces the complexity of searching. It has been built on the Hamming distance based Locality Sensitive Hashing that samples bits of iris code. It reduces both computational and memory costs significantly. Also, it is robust to illumination and occlusion due to eyelids and eyelashes. It has been tested on publicly available database, viz. CASIA-V3-Interval [7]. Further, it has been compared with enhanced geometric hashing [9] technique and it is found to be better in terms of its query response time.
Year
DOI
Venue
2013
10.1109/ICC.2013.6654840
Communications
Keywords
Field
DocType
database indexing,image coding,iris recognition,CASIA-V3-Interval,Hamming distance,enhanced geometric hashing,illumination,indexing technique,iris code hashing,iris database,locality sensitive hashing,occlusion,textural features
Locality-sensitive hashing,Computer vision,Iris recognition,Pattern recognition,Computer science,Search engine indexing,Response time,Hamming distance,Artificial intelligence,Hash function,Geometric hashing,Database index
Conference
ISSN
Citations 
PageRank 
1550-3607
0
0.34
References 
Authors
11
2
Name
Order
Citations
PageRank
Umarani Jayaraman1798.14
Phalguni Gupta280582.58