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Iris Based Recognition System Using Wavelet Transform

机译:基于小波变换的虹膜识别系统

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Iris recognition is known as an inherently reliable technique for human identification. Feature extraction is a crucial step for iris recognition and important task. The extracted features are used for matching. Different wavelet transforms have been used by different researchers for feature extraction in iris recognition. Also many researchers extract features using different coefficient such has horizontal, vertical, diagonal or combination of them. In this work we have used SCOE-Iris v.1 database consisting of 2750 images, acquired in the signal processing laboratory at Sinhgad College of Engineering, Pune, India. In this work different basis wavelet are used for feature extraction and their performance is evaluated. The optimal wavelet transform is determined. Experimental results show that this algorithm are efficient and gives acceptable accuracy.
机译:虹膜识别是人类固有的可靠技术。特征提取是虹膜识别和重要任务的关键步骤。提取的特征用于匹配。不同的研究人员已将不同的小波变换用于虹膜识别中的特征提取。同样,许多研究人员使用不同的系数提取特征,例如水平,垂直,对角线或它们的组合。在这项工作中,我们使用了由2750张图像组成的SCOE-Iris v.1数据库,该数据库是从印度普那Sinhgad工程学院的信号处理实验室获得的。在这项工作中,将不同的基波用于特征提取并评估其性能。确定最佳小波变换。实验结果表明,该算法是有效的,并且给出了可接受的精度。

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