Biosens Bioelectron, an open access journal ISSN 2577-2260 1 Volume 2018; Issue 05 Biosensors and Bioelectronics Open Access Research Article Garea-Llano E, et al. Biosens Bioelectron Open Acc: BBOA-144. Image Quality Evaluation for Video Iris Recognition in the Visible Spectrum Eduardo Garea-Llano 1* , Dailé Osorio-Roig 1 , Osdel Hernandez-Hernandez 2 1 Advanced Technologies Application Center (CENATAV), Rpto. Siboney, Playa, La Habana, Cuba 2 Faculty of Mathematics and Computing, University of Havana San Lázaro & L, Vedado, Havana, Cuba * Corresponding author: Eduardo Garea-Llano, Advanced Technologies Application Center (CENATAV), 7a # 21406 e/ 214 y 216, Rpto. Siboney, Playa, C.P. 12200, La Habana, Cuba. Tel: +5372714787; Email: egarea@cenatav.co.cu Citation: Garea-Llano E, Osorio-Roig D, Hernandez-Hernandez O (2018) Image Quality Evaluation for Video Iris Recognition in the Visible Spectrum. Biosens Bioelectron Open Acc: BBOA-144. DOI: 10.29011/ 2577-2260.100044 Received Date: 16 August, 2018; Accepted Date: 06 September, 2018; Published Date: 12 September, 2018 Abstract Video-based eye image acquisition in the visible spectrum for iris recognition has taken great importance in the current context of the extensive use of video surveillance cameras and mobile devices. This modality can provide more information from the video capture of the eye region, but it is essential that the images captured have a quality that allows an effective recognition process. In this work, an approach for video iris recognition in the visible spectrum is presented. It is based on a scheme whose novelty is in the possibility of evaluating the quality of the eye image simultaneously with the process of video capturing. A measure of image quality that takes into account the elements defned in the ISO / IEC 19794-6 2005 standard and its combination with automatic detection methods is proposed. The experiments developed on three international databases and own video database demonstrate the relevance of the proposal. DOI: 10.29011/ 2577-2260. 00044 Keywords: Iris Recognition; Quality Measure; Video Introduction Near-Infra-Red (NIR) light (in the range of 780 nm to 840 nm) is capable of effectively capturing the iris pattern since light in this range is scattered in the internal structures of the iris regardless of the color it is, or the possible low contrast between the iris and the pupil in those individuals with dark irises. However, most commercial sensors, such as video surveillance cameras, do not have NIR sensors to perform this type of capture. On the other hand, the rise of mobile devices such as smart phones and their integrated cameras are already used for various biometric applications. Nevertheless, in the case of iris biometry this can be hampered by the limiting factor of not having NIR sensors. Therefore, if you intend to use a sensor that works in the visible spectrum (in the range of 380 nm to 720 nm) to capture iris patterns, the success could be limited only to those instances of light color iris and that are captured in a controlled scenario. In view of the growing popularity of iris biometry based on this type of sensor [1], it is important to address this problem due to the wide spectrum of applications that can be developed. The acquisition of video- based eye images for iris recognition is an interesting alternative in the current context of the extensive use of mobile devices and video surveillance cameras [2,3]. This modality can provide more information from video capture of eye region. The problem in these systems is the generated large amount of information from the video capture and how to decide what information will be passed to the system in order to perform the recognition process. A metric for evaluating the quality of eye images combined with automatic image detection can be an alternative. In this work, an approach for video iris recognition is proposed; it is based on a scheme whose novelty is in the possibility of evaluating the quality of the eye image in real time simultaneously with process of video capture. For this purpose, a measure of eye image quality is proposed, it takes into account the elements defned in the ISO/ IEC 19794-6: 2005 standard [4]. The combination of the proposed measure with automatic eye detection method ensures that eye images are extracted so that they do not have elements that negatively infuence the identifcation process such as closed eyes and out-of-angle look. The work is structured as fallows. Section 2 discuss the related works, section 3 presents the proposed approach, in section 4 the experimental results are presented and discussed, and fnally the conclusions of the work are set.