Results 11 to 20 of about 45,283 (277)
Iris Localization Algorithm based on Effective Area
International Journal of Antennas and Propagation, 2021 Iris localization is the most crucial part of the iris processing because its accuracy can directly affect the accuracy of biometric identification in subsequent steps.
Jinfeng Yu, Lei Zhang, Zhi Wang
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An Improved Iris Localization Method
The International Arab Journal of Information Technology, 2022 Iris research has become an inevitable trend in the application of identity recognition due to its uniqueness, stability, non-aggression and other advantages. In this paper, an improved iris localization method is presented. When the iris inner boundary is located, a method for extracting the iris inner boundary based on morphology operations with ...
Meisen Pan, Qi Xiong
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Iris identification based on a local analysis of the iris texture [PDF]
2009 Proceedings of 6th International Symposium on Image and Signal Processing and Analysis, 2009 This paper focuses on a new iris identification method based on a local analysis of the iris texture. In the method, the iris is divided in sub-regions, using locally sliding windows, to extract local signatures. Local distances are then calculated and fused, based on a weighting average.
Adam, Mathieu +3 more
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IEEE Access, 2020 Iris center localization is the basis of iris biometrics, face recognition and gaze tracking. However, individual differences, changes in facial expression, varying light conditions, occlusion, and so on, all bring great challenges to accurately localize
Lihong Dai +3 more
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Model-based pupil and iris localization [PDF]
The 2012 International Joint Conference on Neural Networks (IJCNN), 2012 The iris is the most accurate biometric to date and its localization is a vital step in any iris recognition system. Iris localization can be considered as the search for the demarcation points, or step change in intensity at its boundaries. A failed localization will lead to incorrect iris segmentation and eventually to poor recognition.
Nitin K. Mahadeo +2 more
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Iris localization by means of adaptive thresholding and Circular Hough Transform [PDF]
Journal of Artificial Intelligence and Data Mining, 2017 In this paper, a new iris localization method for mobile devices is presented. Our system uses both intensity and saturation threshold on the captured eye images to determine iris boundary and sclera area, respectively.
S. Memar Zadeh, A. Harimi
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IMPROVING IRIS RECOGNITION ACCURACY USING GABOR KERNELS WITH NEAR-HORIZONTAL ORIENTATIONS
International Journal of Advances in Signal and Image Sciences, 2022 extraction of iris features. However, the selection of Gabor kernel orientations remains an important key for an optimum performance. In this paper, Gabor kernels with horizontal and two near-horizontal orientations (0°, 15°, 165°) are used for ...
Ahmed AK. Tahir, Steluta Anghelus
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Human Iris Recognition using Elman Neural Networks [PDF]
مجلة التربية والعلم, 2010 The human iris is one of the best biometric features in the human body for pattern recognition. In this paper, the iris recognition system is described that consist of two main parts: image processing and its recognition.
Shaymaa Al-mashahadany
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High Biometric Recognition Based on Histogram and Semi-discrete Matrix Decomposition via Neural Network [PDF]
Engineering and Technology Journal, 2016 Iris recognition is regarded as the most reliable and accurate biometric identification system available highly protected and stable.Iris situating is the main focus in the procedure of iris recognition and verifies the precision of identification.
Ekbal Hussein Ali +2 more
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Circle-based Eye Center Localization (CECL) [PDF]
, 2015 We propose an improved eye center localization method based on the Hough transform, called Circle-based Eye Center Localization (CECL) that is simple, robust, and achieves accuracy on a par with typically more complex state-of-the-art methods.
Maes, Alfons +2 more
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