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Human Authentication Algorithm using Spectral Feature of Retinal Fundus Image

Mahrokh Khakzar, Hossein Pourghassem


In this paper, a retina Authentication algorithm based on tessellation of frequency spectrum is developed. This algorithm proposed a tessellation scheme, By applying this tessellation on Two-dimensional Discrete Fourier Transform of retina image, we can extract a rotation invariant, multi resolution and optimized features with low computational for our retina Authentication algorithm. The proposed algorithm is structured in three parts namely vessel segmentation, feature extraction and decision making. First step is dividing retinal image to vessel or non-vessel for this purpose, we use a fast and accruable algorithm to segment the retina image to vessel and non- vessel. Second step is forming feature vectors by applying proposed tessellation scheme on frequency spectrum of vessel skeleton of retinal image. Then, a specific scenario is defined based on energy spectrum of vessels to identify each individual. Finally, Euclidean distance criterion is used to evaluate the accuracy of proposed tessellation scheme. Experimental results show that the proposed technique obtains the accuracy rate of 99.29 % in presence of rotation and multi resolution samples.


Authentication, tessellation-based spectral feature; retinal image; energy spectrum, radial partitioning.

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