A Robust Person Authentication System based on Score Level Fusion of Left and Right Irises and Retinal Features
L. latha,S. Thangasamy +1 more
TLDR
A multimodal biometric approach for identity verification using two competent traits, iris and retina, which diminishes the drawback of single biometric system and improves the performance of an authentication system.About:
This article is published in Procedia Computer Science.The article was published on 2010-01-01 and is currently open access. It has received 26 citations till now. The article focuses on the topics: Iris recognition & Eye vein verification.read more
Citations
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Journal ArticleDOI
Retina Verification System Based on Biometric Graph Matching
TL;DR: An automatic retina verification framework based on the biometric graph matching (BGM) algorithm, which achieves complete separation on a training set of images from the VARIA database, equaling the state-of-the-art for retina verification.
Journal ArticleDOI
Comparative study of multimodal biometric recognition by fusion of iris and fingerprint.
TL;DR: The experimental results suggest that the fuzzy logic method for the matching scores combinations at the decision level is the best followed by the classical weighted sum rule and the classical sum rule in order.
Proceedings ArticleDOI
Investigating Mobile Device Picking-up motion as a novel biometric modality
Tao Feng,Xi Zhao,Weidong Shi +2 more
TL;DR: Two novel methods are proposed, a Statistic Method to intuitively apply classifier on the statistic features of the data; and a Trajectory Reconstruction Method to reconstruct the Mobile Device Picking-up motion trajectories and extract specific identity features from the traces.
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A high performance hardware architecture for portable, low-power retinal vessel segmentation
TL;DR: The low power consumption of the proposed VLSI implementation enables the proposed architecture to be used in portable systems, as it achieves an efficient balance between performance, power consumption and accuracy.
Proceedings ArticleDOI
Retina features based on vessel graph substructures
TL;DR: It is shown that combining nodes and edges can improve the distance and two retina graph statistics, the edge-to-node ratio and the variance of the degree distribution, that have low correlation with node match score are identified.
References
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Book
Digital Image Processing Using MATLAB
TL;DR: 1. Fundamentals of Image Processing, 2. Intensity Transformations and Spatial Filtering, and 3. Frequency Domain Processing.
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On combining classifiers
TL;DR: A common theoretical framework for combining classifiers which use distinct pattern representations is developed and it is shown that many existing schemes can be considered as special cases of compound classification where all the pattern representations are used jointly to make a decision.
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How iris recognition works
TL;DR: Algorithms developed by the author for recognizing persons by their iris patterns have now been tested in many field and laboratory trials, producing no false matches in several million comparison tests.
Proceedings ArticleDOI
How iris recognition works
TL;DR: Algorithms developed by the author for recognizing persons by their iris patterns have now been tested in many field and laboratory trials, producing no false matches in several million comparison tests.