Biometric gateways are used to quickly and accurately identify people. Of the biometric characteristics, iris, face and fingerprints are commonly used. By combining them, better identification results can be achieved. The aim of this thesis is to create such a biometric gateway together with the control application. A combination of iris of both eyes and face is used, which is captured by cameras from three angles to increase accuracy. Neural networks are used to detect and extract face features. Iris recognition is realized using Daugman's algorithm.

The biometric techniques are well known and widespread nowadays. In this context biometry means automated person recognition using anatomic features. This work uses the iris as the anatomic feature. Iris recognition is taken as the most promising technique of all because of its non-invasiveness and low error rate. The inventor of iris recognition is John G. Daugman. His work underlies almost all current public works of this technology. This final thesis is concerned with biometry based on iris images. The principles of biometric methods based on iris images are described in the first part. The first practical part of this work is aimed at the proposal and realization of two methods which localize the iris inner boundary. The third part presents the proposal and realization of iris image processing in order to classifying persons. The last chapter is focus on evaluation of experimental results and there are also compared our results with several well-known methods.

In my thesis, I focus on the task of recognizing human iris from an image.In the beginning, the work deals with a question of biometrics, its importance and basic concepts, which are necessary for use in following text. Subsequently process of human Iris detection is described together with theory of evolution algorithms. In the implementation part, is described the design of implemented solution, which uses evolution algorithms, where is emphasis on correct pupil and iris boundary detection.