Abstract
In this paper, we propose an iris detection and localization method based on AdaBoost algorithm and neural networks with local interconnection structures to overcome the limits in the current iris detection and localization algorithms. It has three features: Firstly, according to the features of the iris image, we design a set of local interconnection neural networks iris classifiers with different receptive fields and different complexity. Secondly, we use AdaBoost algorithm to integrate neural networks classifiers to generate a chief classifier with powerful iris detection ability. Thirdly, cascade connection structure is applied to increase the detection speed. Experimental results show that this algorithm has very high detection accuracy and speed. It can solve the iris detection and localization problems efficiently in the case of with large face region and cataract patients
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
