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A Quality Assessment Method of Iris Image Based on Support Vector Machine

机译:基于支持向量机的虹膜图像质量评估方法

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摘要

The quality of iris image is one of the key factors in uences the performance of iris pattern recognition. Based on the existing quality assessment measures of iris image, and in consideration of the most prominent factors that lead recognition to fail, we firstly put forward iris rotation which is a new quality assessment measure. Then iris rotation, iris visibility, iris eccentricity and iris definition are together as quality assessment measures of iris image and the quality assessment of iris image is done by Support Vector Machine (SVM) classifier. The experiment results express that the method we propose can select the images with good quality and has strong predictability for the performance of iris pattern recognition.
机译:虹膜图像质量是影响虹膜模式识别性能的关键因素之一。在现有虹膜图像质量评估方法的基础上,结合导致识别失败的最主要因素,首先提出虹膜旋转是一种新的质量评估方法。然后将虹膜旋转,虹膜可见度,虹膜偏心率和虹膜清晰度一起作为虹膜图像的质量评估手段,并通过支持向量机(SVM)分类器对虹膜图像进行质量评估。实验结果表明,本文提出的方法可以选择高质量的图像,对虹膜模式识别的性能具有很强的可预测性。

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