%0 Conference Paper %1 BIOSIGNALS2009 %A Ferreira, Artur %A Louren�o, Andr� %A Pinto, B�rbara %A Tendeiro, Jorge %B BIOSIGNALS09 %C Porto, Portugal %D 2009 %K Biometrics, Image_Processing, Image_Segmentation Iris_Recognition, %T Modifications and Improvements on Iris Recognition %X Iris recognition is a well-known biometric technique. John Daugman has proposed a method for iris recognition, which is divided into four steps: segmentation, normalization, feature extraction and matching. In this paper, we evaluate, modify and extend John Daugman�s method. We study the images of CASIA and UBIRIS databases to establish some modifications and extensions on Daugman�s algorithm. The major modification is on the computationally demanding segmentation stage, for which we propose a template matching approach. The extensions on the algorithm address the important issue of pre-processing, that depends on the image database, being especially important when we have a non infra-red red camera (e.g. a WebCam). For this typical scenario, we propose several methods for reflexion removal and pupil enhancement and isolation. The tests, carried out by our C# application on grayscale CASIA and UBIRIS images, show that our template matching based segmentation method is accurate and faster than the one proposed by Daugman. Our fast pre-processing algorithms efficiently remove reflections on images taken by non infra-red cameras.

@inproceedings{BIOSIGNALS2009, abstract = {Iris recognition is a well-known biometric technique. John Daugman has proposed a method for iris recognition, which is divided into four steps: segmentation, normalization, feature extraction and matching. In this paper, we evaluate, modify and extend John Daugman�s method. We study the images of CASIA and UBIRIS databases to establish some modifications and extensions on Daugman�s algorithm. The major modification is on the computationally demanding segmentation stage, for which we propose a template matching approach. The extensions on the algorithm address the important issue of pre-processing, that depends on the image database, being especially important when we have a non infra-red red camera (e.g. a WebCam). For this typical scenario, we propose several methods for reflexion removal and pupil enhancement and isolation. The tests, carried out by our C# application on grayscale CASIA and UBIRIS images, show that our template matching based segmentation method is accurate and faster than the one proposed by Daugman. Our fast pre-processing algorithms efficiently remove reflections on images taken by non infra-red cameras.}, added-at = {2009-10-25T20:10:08.000+0100}, address = {Porto, Portugal}, author = {Ferreira, Artur and Louren�o, Andr� and Pinto, B�rbara and Tendeiro, Jorge}, biburl = {https://www.bibsonomy.org/bibtex/260205114206d40a3e3a251f31cfea438/alourenco}, booktitle = {BIOSIGNALS09}, interhash = {c778a824dbbf46daf6393e1d2356411e}, intrahash = {60205114206d40a3e3a251f31cfea438}, keywords = {Biometrics, Image_Processing, Image_Segmentation Iris_Recognition,}, month = {January}, timestamp = {2009-10-25T20:20:15.000+0100}, title = {Modifications and Improvements on Iris Recognition}, year = 2009 }