Abstract
Iris recognition is one of important biometric recognition approach in a human identification is becoming very active topic in research and practical application. In this paper, Gaussian pyramid compression technique is used to compress the eye image and this compressed eye is used for the localization of the inner and outer boundaries of the iris region. Located iris is extracted from the compressed eye image and after normalization and enhancement it is represented by a data set. With Gaussian pyramid compression improved matching performance is observed down to 0.25 bits/pixel (bpp), attributed to noise reduction without a significant loss of texture. To ensure that, the iris-matching algorithms are not degraded by image compression. The proposed method is evaluated using CASIA iris image database version 1.0 [7] and achieved high accuracy of 96%. Experimental results demonstrate that the proposed method can be used for human identification in an efficient manner.
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Savithiri, G., Murugan, A. (2010). Iris Recognition Technique Using Gaussian Pyramid Compression. In: Das, V.V., et al. Information Processing and Management. BAIP 2010. Communications in Computer and Information Science, vol 70. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12214-9_52
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DOI: https://doi.org/10.1007/978-3-642-12214-9_52
Publisher Name: Springer, Berlin, Heidelberg
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