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Noncircular Iris Segmentation Based on Weighted Adaptive Hough Transform Using Smartphone Database

机译:基于使用智能手机数据库的加权自适应Hough变换的非功能虹膜分割

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摘要

Iris segmentation methods work based on ideal imaging conditions which produce good output results. However, the segmentation accuracy of an iris recognition system significantly influences its performance, especially with data that captured in unconstrained environment of the Smartphone. This paper proposes a novel segmentation method for unconstrained environment of the Smartphone videos based on choose the best frames from the videos and try to enhance the contrast of this frames by applying the two fuzzy logic membership functions on the negative image which delimit between dark and bright regions in able to make the dark region darker and the bright region brighter. This pre-processing step Facilitates the work of the Weighted Adaptive Hough Transform to automatically find the diameter of the iris region to apply the osiris v4.1. The proposed method results on the video of (Mobile Iris Challenge Evaluation (MICHE))-I, iris databases indicate a high level of accuracy and more efficient computationally using the proposed technique.
机译:虹膜分割方法基于理想的成像条件,产生良好的输出结果。然而,虹膜识别系统的分割精度显着影响其性能,特别是在智能手机的不受约束环境中捕获的数据。本文提出了一种基于视频中选择最佳帧的智能手机视频的无约束环境的新型分段方法,并尝试通过在深色和明亮之间分隔的负图像上的两个模糊逻辑隶属函数来增强该帧的对比度能够使暗区更暗的地区和明亮的区域更明亮。该预处理步骤有助于加权自适应Hough变换的工作自动找到虹膜区域的直径以应用Osiris v4.1。所提出的方法结果(移动虹膜挑战评估(MICHE)) - I,IRIS数据库指示高水平的精度,并且使用所提出的技术计算更有效。

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