Iris recognition using collarette boundary localization

There has been a rapid increase in the need of accurate and reliable personal identification infrastructure in recent years, and biometrics has become an important technology for security. The iris recognition system consists of four-process: image acquisition, preprocessing, feature extraction and identification or verification. In this paper, we propose the methods for localizing the iris area between the inner boundary and the collarette boundary, to remove unnecessary areas and to increase the recognition rate. For finding the collarette boundary, histogram equalization and a high pass filter, after using an one-dimensional DFT, are applied to the image. The collarette boundary is found using statistical information from the image, which removes low-frequencies, and, finally, the iris is localized between the inner boundary and the collarette boundary. The iris is localized by two kinds of methods, and the recognition rates were compared. The recognition rate was evaluated by using DWT and SVM. These show that the iris localization by the proposed methods contains more information than the previous methods and improves the recognition rate.