On Clinical-Data-Based Personal Identification for Ophthalmological Patients

In this paper, a system of personal identification using data associated with corneal thickness is presented for ophthalmological patients. The data are measured by OCT (Optical Coherence Tomography). The proposed method equally divides the cornea into thirty-two fan-shaped segments, using thirty-two radiuses. It generates a couple of thirty-two dimensional vectors (or a sixty-four-dimensional vector) for some test subject as the registered data, and adds it to a set. Each of the data consists of element values associated with minimum values and/or maximum values on the above radiuses. When the test subject takes medical practice, the proposed method generates two thirty-two-dimensional vectors (or a sixty-four dimensional vector) for the corresponding test subject as the collation data. Then, the proposed method calculates the 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 100 percent as the identification rate on assumption that the number of subjects is at most 45.