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Fuzzy based IRIS recognition system (FIRS) for person identification

机译:基于模糊的IRIS识别系统(FIRS)用于人员识别

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Person identification using iris recognition method is very effective and popular. Existing iris recognition methods have problems because of non-uniform illumination, rotational inconsistencies and noise. An efficient Fuzzy based Iris Recognition Scheme (FIRS) has been proposed in this paper to overcome the above deficiencies. This scheme has four stages namely Segmentation, Normalization, Feature extraction and classification using fuzzy logic. The proposed scheme uses Hough transform for detection of Region Of Interest (ROI), and combination of Discrete Wavelet Transform (DWT) and Independent Component Analysis (ICA) for feature extraction. The proposed scheme has been tested and the results have been reported. It was observed that the proposed method classifies the images with better accuracy and outperforms the existing methods.
机译:使用虹膜识别方法的人识别非常有效和流行。由于不均匀的照明,旋转不一致和噪音,现有的虹膜识别方法存在问题。本文提出了一种高效的基于模糊的虹膜识别方案(FIR)以克服上述缺陷。该方案具有四个阶段即,使用模糊逻辑进行分割,归一化,特征提取和分类。所提出的方案使用Hough变换来检测感兴趣区域(ROI),以及用于特征提取的离散小波变换(DWT)和独立分量分析(ICA)的组合。已经测试了拟议的计划,结果已被检验。观察到所提出的方法通过更好的准确度对图像进行分类,并且优于现有方法。

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