Retina Identification Based on Moment Invariant

Abstract

This paper demonstrates the importance of topics in physics and mathematics courses such as matrix, eigenvectors, centroid, and moment of inertia in the pattern recognition applications.Teaching advance topics in physics and mathematics is not an easy task. Students always ask this question: What is the use? The best practice for teaching these topics is to combine them with a real industry application. For example, computer hard disk reading is based on the concept of derivatives and the change in the magnetic fields. To demonstrate this type of teaching, the use of three dimensional moments in the pattern recognition is explained.The three-dimensional moments may be used to detect different patterns in a digitally represented image. The combination of several moments for an object has an invariant property. The mathematical foundation of an invariant feature is related to the theory that images taken from different angles from the same object have the same set of moment invariants. Moments contain information of an image which can be used in calculating the location and orientation of an object. An algorithm for recognition of an individual identity based on a digitally represented image of the scanned retina is presented. The technology is based upon the fact that no two retinal patterns are alike.In this paper, the nine parameters of an ellipsoidal shape fitted into a retinal image such as coordinates of the center of the ellipsoid, the length of major, minor, intermediate axes, and the direction of three axes will be calculated. For each individual, these parameters are unique.