International Journal of Computer Vision
Finding circles by an array of accumulators
Communications of the ACM
Multidimensional binary search trees used for associative searching
Communications of the ACM
Geometric Hashing: An Overview
IEEE Computational Science & Engineering
High Confidence Visual Recognition of Persons by a Test of Statistical Independence
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image Indexing Using Color Correlograms
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Object Recognition from Local Scale-Invariant Features
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Digital Image Processing (3rd Edition)
Digital Image Processing (3rd Edition)
Use of Artificial Color filtering to improve iris recognition and searching
Pattern Recognition Letters
Iris recognition: an emerging biometric technology
ISPRA'07 Proceedings of the 6th WSEAS International Conference on Signal Processing, Robotics and Automation
Speeded-Up Robust Features (SURF)
Computer Vision and Image Understanding
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
UBIRIS: a noisy iris image database
ICIAP'05 Proceedings of the 13th international conference on Image Analysis and Processing
A human identification technique using images of the iris andwavelet transform
IEEE Transactions on Signal Processing
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Local feature based retrieval approach for iris biometrics
Frontiers of Computer Science: Selected Publications from Chinese Universities
Hi-index | 12.05 |
This paper proposes a hierarchical approach to retrieve an iris image efficiently from for a large iris database. This approach is a combination of both iris color and texture. Iris color is used for indexing and texture is used for retrieval of iris images from the indexed iris database. An index which is determined from the iris color is used to filter out the images that are not similar to the query image in color. Further, iris texture features of those filtered images, are used to determine the images which are similar to the query image. The iris color information helps to design an efficient indexing scheme based on color indices. The color indices are computed by averaging the intensity values of all red and blue color pixels. Kd-tree is used for real-time indexing based on color indices. The iris texture features are obtained through Speeded Up Robust Features (SURF) algorithm. These features are used to get the query's corresponding image at the top best match. The performance of the proposed indexing scheme is compared with two well known iris indexing schemes (Mehrotra, Majhi, & Gupta, 2010; Puhan & Sudha, 2008) on UPOL (Dobes, Machala, Tichavsky, & Pospi'sil, 2004) and UBIRIS (Proencca & Alexandre, 2005) iris databases. It is observed that combination of iris color and texture improves the performance of iris recognition system.