In this paper, a simple personal identification system is presented, using data associated with corneal thickness measured by OCT (Optical Coherence Tomography). The proposed method divides the cornea into thirty two fan-shaped segments, each of which has the same area, using thirty two radiuses. It generates the thirty-two-dimensional (or sixty-four-dimensional) vector for some test subject as the registered data at some time point, and adds it to a set. The data consists of element values equal to minimum values and/or maximum values on the above radiuses. When the test subject takes medical practice, the proposed method generates thirty-two-dimensional (or sixty-four-dimensional) vector for the corresponding test subject as the collation data, and calculates the Euclidean distance between the collation data with each of the vectors in the set. It judges the test subject corresponding to the given collation data to be that of the registered data with the shortest distance to the given data. Experimental results establish that the proposed method achieves one hundred percentage as the identification rate on assumption that the number of test subjects is 30, when element values of the registered data and collation data are associated with pachymetry.
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