Open AccessJournal Article
Iris recognition based on multialgorithmic fusion
Reads0
Chats0
TLDR
The experimental results on CASIA and UBIRIS iris image databases show that the proposed multialgorithmic fusion method can bring obvious performance improvement compared with any single algorithm, and the results also demonstrate that the fusion rule based on SVM can achieve better performance than conventional 1 fusion rules.Abstract:
Fusion of multiple algorithms for biometric verification performance improvement has received considerable attention. This paper proposes an iris recognition method based on multialgorithmic fusion. The proposed method combines the phase information based algorithm and zero-crossing representation based algorithm at the matching score level. The fusion rule based on support vector machine (SVM) is applied to generate a fused score which is used to make the fial decision. The experimental results on CASIA and UBIRIS iris image databases show that the proposed multialgorithmic fusion method can bring obvious performance improvement compared with any single algorithm, and the results also demonstrate that the fusion rule based on SVM can achieve better performance than conventional 1 fusion rules.read more
Citations
More filters
Journal ArticleDOI
A pattern recognition and adaptive approach to quality control
TL;DR: In this article, the authors describe a model which develops a continuous evaluation of product quality using pattern recognition techniques in a dynamic way, it means, they control the variations of critical characteristics of industrial products during their effective use.
Book ChapterDOI
Multi-stage Real-Time Iris Preprocessing
TL;DR: This chapter presents in detail a multistage approach to iris segmentation that addresses the growing demand for real-time capable solutions in the field of Iris segmentation.
Book ChapterDOI
Image Compression Impact on Iris Recognition
TL;DR: Detailed investigations of the effect of image compression on iris biometrics in order to provide an efficient storage and rapid transmission of biometric records are motivated.
Book ChapterDOI
Experiments on Iris Biometric Template Protection
TL;DR: Experimental investigations comprise performance evaluations of different types of iris biometric cryptosystems as well as cancelable irIS biometrics, giving an overview of different approaches to irisBiometric template protection at a glance.
Proceedings ArticleDOI
Fusion of multispectral palmprint images for automatic person identification
TL;DR: This paper presents a novel biometric technique to automatic personal identification system using multispectral palmprint technology, and shows that the proposed method achieve an excellent identification rate and provide more security.
References
More filters
Book
The Nature of Statistical Learning Theory
TL;DR: Setting of the learning problem consistency of learning processes bounds on the rate of convergence ofLearning processes controlling the generalization ability of learning process constructing learning algorithms what is important in learning theory?
Book
Characterization of Signals From Multiscale Edges
Stéphane Mallat,S. Zhong +1 more
TL;DR: The authors describe an algorithm that reconstructs a close approximation of 1-D and 2-D signals from their multiscale edges and shows that the evolution of wavelet local maxima across scales characterize the local shape of irregular structures.
Journal 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.
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.
Journal ArticleDOI
Information fusion in biometrics
Arun Ross,Anil K. Jain +1 more
TL;DR: This paper addresses the problem of information fusion in biometric verification systems by combining information at the matching score level by combining three biometric modalities (face, fingerprint and hand geometry).