http://dl.gi.de/handle/20.500.12116/20078 Sun, 06 Sep 2026 20:24:41 GMT 2026-09-06T20:24:41Z http://dl.gi.de:80/bitstream/id/37d47151-0704-4875-a15f-17d2bb7fe332/ http://dl.gi.de/handle/20.500.12116/20078 http://dl.gi.de/handle/20.500.12116/18322 Image metric-based biometric comparators: a supplement to feature vector-based Hamming distance? Hofbauer, Heinz; Rathgeb, Christian; Uhl, Andreas; Wild, Peter Brömme, Arslan; Busch, Christoph In accordance with the ISO/IEC FDIS 19794-6 standard an iris-biometric fusion of image metric-based and Hamming distance (HD) comparison scores is presented. In order to demonstrate the applicability of a knowledge transfer from image quality assessment to iris recognition, Peak Signal to Noise Ratio (PSNR), Structural Similarity Index Measure (SSIM), Local Edge Gradients metric (LEG), Edge Similarity Score (ESS), Local Feature Based Visual Security (LFBVS), and Visual Information Fidelity (VIF) are applied to iris textures, i.e. query textures are interpreted as noisy representations of registered ones. Obtained scores are fused with traditional HD scores obtained from iris-codes generated by different feature extraction algorithms. Experimental evaluations on the CASIA-v3 iris database confirm the soundness of the proposed approach. Sun, 01 Jan 2012 00:00:00 GMT http://dl.gi.de/handle/20.500.12116/18322 2012-01-01T00:00:00Z http://dl.gi.de/handle/20.500.12116/18324 Evaluation of automatic face recognition for automatic border control on actual data recorded of travellers at Schiphol Airport Spreeuwers, Luuk J.; Hendrikse, Anne J.; Gerritsen, Kier-Co J. Brömme, Arslan; Busch, Christoph Automatic border control at airports using automated facial recognition for checking the passport is becoming more and more common. A problem is that it is not clear how reliable these automatic gates are. Very few independent studies exist that assess the reliability of automated facial recognition for border control. In this evaluation study the reliability of automated facial recognition for automatic border passage was investigated. To investigate the quality of the images and face recognition, during 2 weeks data of real passengers were acquired at Schiphol Airport using 2 different automatic gates of about 950 passengers for both gates. This data alone already makes the evaluation study of great value. The evaluation experiment consisted of comparing live images of every passenger to the digital photographs stored on their passports. Every live image is compared to every digital passport photograph. In this way we can estimate both the False Accept Rate as well as the Verification Rate. In spite of the critical analysis in this study, the prospects for automatic border passage using face recognition are very good. We expect that, provided that the quality of the live images acquired by the gates is improved and if possible the quality of the digital photographs stored on the passport, excellent recognition results can be obtained with Verification Rates (VR) of above 99% at a False Accept Rate (FAR) of 0.1% or even lower. Sun, 01 Jan 2012 00:00:00 GMT http://dl.gi.de/handle/20.500.12116/18324 2012-01-01T00:00:00Z http://dl.gi.de/handle/20.500.12116/18323 Fingerphoto recognition with smartphone cameras Stein, Chris; Nickel, Claudia; Busch, Christoph Brömme, Arslan; Busch, Christoph This paper is concerned with the authentication of people on smartphones using fingerphoto recognition. In this work, fingerphotos are captured with the built-in camera of the smartphone. The proposed authentication method is analyzed for feasibility and implemented in a prototype as application for the Android operating system. Algorithms for the capture process are developed to ensure a minimum of quality of the captured photos to enable a reliable fingerphoto recognition. Several methods for preprocessing of the captured samples are analyzed and performant solutions to evaluate the photos are developed to enhance the recognition rates. This is achieved by evaluating a wide range of different parameters and configurations of the algorithms as well as various combinations of preprocessing chains for the captured samples. The operations for preprocessing are selected with respect to their computational effort to guarantee that they can be executed on a smartphone with limited computation and memory capacity. The developed prototype is evaluated in user tests with two different smartphones. Additionally, a biometric database containing photos of the two test devices from 41 test subjects is created. These fingerphotos are used to evaluate and optimize the procedures. Sun, 01 Jan 2012 00:00:00 GMT http://dl.gi.de/handle/20.500.12116/18323 2012-01-01T00:00:00Z http://dl.gi.de/handle/20.500.12116/18321 How a local quality measure can help improving iris recognition Cremer, Sandra; Dorizzi, Bernadette; Garcia-Salicetti, Sonia; Lempérière, Nadège Brömme, Arslan; Busch, Christoph The most common iris recognition systems extract features from the iris after segmentation and normalization steps. In this paper, we propose a new strategy to select the regions of normalized iris images that will be used for feature extraction. It consists in sorting different sub-images of the normalized images according to a GMM-based local quality measure we have elaborated and selecting the N best sub-images for feature extraction. The proportion of the initial image that is kept for feature extraction has been set in order to compromise between minimizing the amount of noise taken into account for feature extraction and maximizing the amount of information available for matching. By proceeding this way, we privilege the regions for which our quality measure gives the highest values, namely regions of the iris that are highly textured and free from occlusion, and minimize the risks of extracting features in occluded regions to which our quality measure gives the lowest values. We also control the amount of information we use for matching by including, if necessary, regions that are given intermediate values by our quality measure and are free from occlusion but barely textured. Experiments were performed on three different databases: ND-IRIS- 0405, Casia-IrisV3-Interval and Casia-IrisV3-Twins, and show a significant improvement of recognition performance when using our strategy to select regions for feature extraction instead of using a binary segmentation mask and considering all unmasked regions equally. Sun, 01 Jan 2012 00:00:00 GMT http://dl.gi.de/handle/20.500.12116/18321 2012-01-01T00:00:00Z