DEPENDENCY OF OPTIMAL PARAMETERS OF THE IRIS TEMPLATE ON IMAGE QUALITY AND BORDER DETECTION ERROR

Abstract. Generation of a template containing spatial-frequency features of iris is an important stage of identification. The template is obtained by a wavelet transform in an image region specified by iris borders. One of the main characteristics of the identification system is the value of recognition error, equal error rate (EER) is used as criterion here. The optimal values (in sense of minimizing the EER) of wavelet transform parameters depend on many factors: image quality, sharpness, size of characteristic objects, etc. It is hard to isolate these factors and their influences. The work presents an attempt to study an influence of following factors to EER: iris segmentation precision, defocus level, noise level. Several public domain iris image databases were involved in experiments. The images were subjected to modelled distortions of said types. The dependencies of wavelet parameter and EER values from the distortion levels were build. It is observed that the increase of the segmentation error and image noise leads to the increase of the optimal wavelength of the wavelets, whereas the increase of defocus level leads to decreasing of this value.