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IS_IS: Iris Segmentation for Identification Systems
2010 20th International Conference on Pattern Recognition, 2010Advances in processing procedures make the iris a realistic candidate to the role of biometry of the future. Precise detection and segmentation for such biometry are a crucial ongoing research area. We propose an iris segmentation technique and show that it is more reliable than existent ones.
Maria De Marsico +2 more
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Highly Usable and Accurate Iris Segmentation
2014 22nd International Conference on Pattern Recognition, 2014Iris segmentation is driven by three different quality factors: accuracy, usability and speed. Unfortunately the deeply analysis of the literature shows that the greatest efforts of the researchers mainly focus on accuracy and speed. Proposed solutions, in fact, do not meet the usability requirement since they are based on specific optimizations ...
Leo Marco +2 more
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Measuring the Quality of IRIS Segmentation for Improved IRIS Recognition Performance
2012 Eighth International Conference on Signal Image Technology and Internet Based Systems, 2012In this paper, we present three versions of an open source software for biometric iris recognition called OSIRIS_V2, OSIRIS_V3, OSIRIS_V4 which correspond to different implementations of J. Daugman's approach. The experimental results on the database ICE2005 show that OSIRIS_V4 is the most reliable on difficult images while OSIRIS_V2 is the fastest. So,
Raida Hentati +3 more
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Consensual Iris Segmentation Fusion
2017Recent works have shown that fusion at segmentation level has contributed to the robustness in iris recognition compared with the one obtained from a single segmentation, due to different segmentation algorithms can produce different segmentations of a same eye image.
Dailé Osorio Roig, Eduardo Garea Llano
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Iris recognition based on robust iris segmentation and image enhancement
International Journal of Biometrics, 2012A new iris recognition method based on a robust iris segmentation approach is presented in this paper for improving iris recognition performance. The robust iris segmentation approach applies power-law transformations for more accurate detection of the pupil region, which significantly reduces the candidate limbic boundary search space for increasing ...
Abhishek Verma +4 more
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Iris Detection through Watershed Segmentation
2014In this paper, we present a new iris detection method based on the use of watershed segmentation. The watershed transform is used for both pupil and iris detection, in combination with image quantization, aimed at reducing the number of gray levels, and image thresholding, aimed at discriminating foreground and background. The method has been tested on
FERONE, Alessio +3 more
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Real Time Iris Segmentation on FPGA
2012 IEEE 23rd International Conference on Application-Specific Systems, Architectures and Processors, 2012In this paper, a real time FPGA-based iris segmentation system is presented. The segmentation method implements the Canny edge detection algorithm and a circle search to detect an iris in an image or video frame. The proposed high performance architecture utilizes on-chip memory to significantly improve the throughput of the pipelined and parallel ...
Hau T. Ngo +4 more
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Iris segmentation using game theory
Signal, Image and Video Processing, 2010Robust segmentation of an iris image plays an important role in iris recognition. However, the nonlinear deformations, pupil dilations, head rotations, motion blurs, reflections, nonuniform intensities, low image contrast, camera angles and diffusions, and presence of eyelids and eyelashes often hamper the conventional iris/pupil localization methods ...
Kaushik Roy 0002 +2 more
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Iris Segmentation Methodologies
2012Traditional iris processing following Daugman’s approach [116] extracts binary features after mapping the textural area between inner pupillary and outer limbic boundary into a doubly dimensionless representation.
Christian Rathgeb +2 more
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2012
Under ideal image acquisition conditions, the iris biometric has been observed to provide high recognition performance compared to other biometric traits. Such a performance is possible by accurately segmenting the iris region from the given ocular image. This chapter discusses the challenges associated with the segmentation process, along with some of
Raghavender Jillela, Arun A. Ross
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Under ideal image acquisition conditions, the iris biometric has been observed to provide high recognition performance compared to other biometric traits. Such a performance is possible by accurately segmenting the iris region from the given ocular image. This chapter discusses the challenges associated with the segmentation process, along with some of
Raghavender Jillela, Arun A. Ross
openaire +1 more source