An Algorithm for Finding Best Matches in Logarithmic Expected Time
ACM Transactions on Mathematical Software (TOMS)
Multidimensional binary search trees used for associative searching
Communications of the ACM
Geometric Hashing: An Overview
IEEE Computational Science & Engineering
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Handbook of Biometrics
Image understanding for iris biometrics: A survey
Computer Vision and Image Understanding
Speeded-Up Robust Features (SURF)
Computer Vision and Image Understanding
Indexing Multimodal Biometric Databases Using Kd-Tree with Feature Level Fusion
ICISS '08 Proceedings of the 4th International Conference on Information Systems Security
Journal of Computer and System Sciences
Coarse iris classification using box-counting to estimate fractal dimensions
Pattern Recognition
Robust iris indexing scheme using geometric hashing of SIFT keypoints
Journal of Network and Computer Applications
Encyclopedia of Biometrics
Iris-Biometric Hash Generation for Biometric Database Indexing
ICPR '10 Proceedings of the 2010 20th International Conference on Pattern Recognition
Real-time iris segmentation based on image morphology
Proceedings of the 2011 International Conference on Communication, Computing & Security
Global texture analysis of iris images for ethnic classification
ICB'06 Proceedings of the 2006 international conference on Advances in Biometrics
An efficient color and texture based iris image retrieval technique
Expert Systems with Applications: An International Journal
Indexing biometric databases using pyramid technique
AVBPA'05 Proceedings of the 5th international conference on Audio- and Video-Based Biometric Person Authentication
A Fast Search Algorithm for a Large Fuzzy Database
IEEE Transactions on Information Forensics and Security
IEEE Transactions on Circuits and Systems for Video Technology
Coarse Iris classification by learned visual dictionary
ICB'07 Proceedings of the 2007 international conference on Advances in Biometrics
Fingerprint indexing with bad quality areas
Expert Systems with Applications: An International Journal
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This paper proposes an efficient retrieval approach for iris using local features. The features are extracted from segmented iris image using scale invariant feature transform (SIFT). The keypoint descriptors extracted from SIFT are clustered into m groups using k-means. The idea is to perform indexing of keypoints based on descriptor property. During database indexing phase, k-d tree k-dimensional tree is constructed for each cluster center taken from N iris images. Thus for m clusters, m such k-d trees are generated denoted as t i , where 1 驴 i 驴 m. During the retrieval phase, the keypoint descriptors from probe iris image are clustered into m groups and ith cluster center is used to traverse corresponding t i for searching. k nearest neighbor approach is used, which finds p neighbors from each tree (t i ) that falls within certain radius r centered on the probe point in k-dimensional space. Finally, p neighbors from m trees are combined using union operation and top S matches (S ⊆ (m脳 p)) corresponding to query iris image are retrieved. The proposed approach has been tested on publicly available databases and outperforms the existing approaches in terms of speed and accuracy.