Image processing
| dc.contributor.advisor | Fazekas, Gábor | |
| dc.contributor.author | Moghadasi, Mohammad | |
| dc.contributor.department | DE--TEK--Informatikai Kar | hu_HU |
| dc.date.accessioned | 2012-06-01T08:37:58Z | |
| dc.date.available | 2012-06-01T08:37:58Z | |
| dc.date.created | 2012 | |
| dc.date.issued | 2012-06-01T08:37:58Z | |
| dc.description.abstract | Biometrics-based authentication systems that use physiological and/or behavioral traits (e.g., fingerprint, face, and signature) are good alternatives to traditional methods. In spite of these advantages of biometric systems over traditional systems, there are many unresolved issues associated with the former. For example, how secure are biometric systems against attacks? How can we guarantee the integrity of biometric templates? How can we use biometric components in traditional access control frameworks? How can we combine cryptography with biometrics to increase overall system security? In this thesis, we address these issues and develop techniques to eliminate associated problems. Firstly, we analyze structure of biometric-based authentication systems and vulnerability of these systems and develop a method for increasing the security of image-based (e.g., fingerprint and face) biometric templates. For many years fractals were used for image compression. In the last few years they have also been used for object recognition. Fractal codes have been used as features for recognition, but we need to take into account the distance between codes, and to ensure the continuity of the parameters of the code. We use a method based on fractal image coding for face and fingerprint recognition. Generally, there are two approaches to using fractal image coding for recognition. The first type uses the fractal code itself, and discrimination comes from differences between the codes. The fractal code of an image is the parameters of a Partitioned Iterated Function System code generated for that image. The second type uses the decoding process of fractal image coding to perform recognition. It is more difficult to use the first type for recognition because fractal codes can change dramatically even between very similar images. The problem is that more than one fractal code can be generated for a given image. An advantage of using the second approach over the first is that we do not have to worry about the uniqueness and distance between codes. We only require the uniqueness of the attractor, which is already an implied property of a properly generated fractal code. ix This thesis focuses on the second approach, from which we develop a distance measure. Compared to other methods, research into fractal image coding based recognition methods has been scarce. Other advantages of this method are: increasing security because use of fractal codes instead of original images, compare fractal codes after decoding process and needless to compare geometrical parameters and non execution heavy preprocessing operation. Error rate in fingerprint verification is 7.1% and results in face verification in spite of different face expression are very acceptable. | hu_HU |
| dc.description.course | Computer science and information technology | hu_HU |
| dc.description.degree | Msc | hu_HU |
| dc.format.extent | 94 | hu_HU |
| dc.identifier.uri | http://hdl.handle.net/2437/129735 | |
| dc.language.iso | en | hu_HU |
| dc.subject | Biometric | hu_HU |
| dc.subject.dspace | DEENK Témalista::Informatika::Műszaki informatika | hu_HU |
| dc.title | Image processing | hu_HU |
| dc.title.subtitle | Provide a new method for increasing the security of identification systems based on biometric data | hu_HU |