Biometrics is constantly evolving technology which has been widely used in many official and commercial identification applications. In fact in recent years biometric-based authentication techniques received more attention due to increased concerns in security. Most biometric systems that are currently in use typically employ a single biometric trait. Such systems are called unibiometric systems. Despite considerable advances in recent years, there are still challenges in authentication based on a single biometric trait, such as noisy data, restricted degree of freedom, intra-class variability, non-universality, spoof attack and unacceptable error rates. Some of the challenges can be handled by designing a multimodal biometric system. Multimodal biometric systems are those which utilize or are capable of utilizing, more than one physiological or behavioural characteristic for enrolment, verification, or identification. In this thesis, we propose a novel fusion approach at a hybrid level between iris and online signature traits. Online signature and iris authentication techniques have been employed in a range of biometric applications. Besides improving the accuracy, the fusion of both of the biometrics has several advantages such as increasing population coverage, deterring spoofing activities and reducing enrolment failure. In this doctoral dissertation, we make a first attempt to combine online signature and iris biometrics. We principally explore the fusion of iris and online signature biometrics and their potential application as biometric identifiers. To address this issue, investigations is carried out into the relative performance of several statistical data fusion techniques for integrating the information in both unimodal and multimodal biometrics. We compare the results of the multimodal approach with the results of the individual online signature and iris authentication approaches. This dissertation describes research into the feature and decision fusion levels in multimodal biometrics.

This master’s thesis gives a description of fundus camera as a medical imaging system. Sub features of this system are explained in short, thus examples of certain construction variants are given. Furthermore, the work deals with image fusion and associated possibilities of digital image processing. One set of consecutive scanned images of human eye’s retina has been provided for the practical part of this work. During program processing of these data, decomposition of obtained images to single-color sequences is performed. For these partial monochromatic sequences, monomodal registration is performed, based on calculation of the brightness similarity criterion between the pairs of images. From the three created monochromatic sequences of registered images, new sequence of color images is created, using multimodal registration of each image triples. As a basis for similarity evaluation during multimodal registration, an information similarity criterion was used.