Paper Info
Title
Indexing Scheme for Iris Using Discrete Cosine and Discrete Wavelet Transform.
Abstract
In this paper, we proposed indexing scheme for Iris image database. We used Discrete Cosine Transformation (DCT) and Discrete Wavelet Transformation (DWT) successively on the normalized Iris image to compute the feature vector of Iris image. DCT and DWT are performed block wise on the normalized Iris image. Based on feature vector of Iris image, we constructed adaptive sized bin, so that each bin consist equal number of images. Interval of the bin is computed using Gaussian distribution approximation. The use of these type of bins improve the penetration rate. The bin number for each index of the feature vector is obtained to form the global key for each image. During database preparation the key is used to traverse the B-tree. The images with same key are stored in the same leaf node. For a given query image, the key is generated and tree is traversed to end up to a leaf node. The templates stored at the leaf node are retrieved and compared with the query template to find the best match. The proposed indexing scheme is showing considerably low penetration rate of 0.0006%, for UBIris.v1.
Year
DOI
Venue
2011
10.1007/978-81-322-0491-6_37
PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON SOFT COMPUTING FOR PROBLEM SOLVING (SOCPROS 2011), VOL 2
Keywords
Field
DocType
DCT,DWT,Indexing,Biometrics,B-tree
Feature vector,Lapped transform,Pattern recognition,Lifting scheme,Computer science,Discrete cosine transform,Transform coding,Second-generation wavelet transform,Discrete wavelet transform,Artificial intelligence,Stationary wavelet transform
Conference
Volume
ISSN
Citations 
131
1867-5662
0
PageRank 
References 
Authors
0.34
7
2
Name
Order
Citations
PageRank
Himanshu120.77
Balasubramanian Raman267970.23