Performance Analysis and Evaluation of Image Enhancement Techniques for Automatic Fingerprint Recognition System using Minutiae Extraction
| dc.contributor.advisor | Dereje, Hailemariam (PhD) | |
| dc.contributor.author | Tesfay, Haftu | |
| dc.date.accessioned | 2019-05-30T09:54:52Z | |
| dc.date.accessioned | 2023-11-28T14:09:10Z | |
| dc.date.available | 2019-05-30T09:54:52Z | |
| dc.date.available | 2023-11-28T14:09:10Z | |
| dc.date.issued | 2018-10 | |
| dc.description.abstract | The use of biometric recognition is increasing nowadays because the characteristics of biometrics are unique and immutable. Traditional identification methods like tokens and access cards are less reliable than the biometric identifiers because their passwords and personal identifications can be forgotten or stolen electronically. Fingerprint is one of the most widely accepted and reliable biometric personal identification method and is unique even for identical twins. This thesis work mainly aims on the performance analysis of enhancement techniques used for reliable and high recognition rate automatic fingerprint recognition system (AFRS). The system is executed using the features that make every individual unique. The system accepts a gray scale low quality fingerprint image as an input, enhances the image using the combination of fast Fourier transform (FFT) and Gabor filter to level up its quality. Then features are extracted from a skeletonized binary image and then these features are used to identify who the person is. The performance measurement metrices of the image enhancement techniques are the number of features detected, computational time, system error rates namely the false match rate (FMR), false non match rate (FNMR) and EER. The MATLAB simulation result shows that the combination of FFT cascaded with Gabor filter gives an accuracy of 95.5 % which is better than the FFT and Gabor filter applied independently. | en_US |
| dc.identifier.uri | http://etd.aau.edu.et/handle/12345678/18343 | |
| dc.language.iso | en_US | en_US |
| dc.publisher | Addis Ababa University | en_US |
| dc.subject | Biometric Recognition | en_US |
| dc.subject | Minutiae | en_US |
| dc.subject | Feature Extraction | en_US |
| dc.subject | Fingerprint | en_US |
| dc.subject | Gabor Filter | en_US |
| dc.title | Performance Analysis and Evaluation of Image Enhancement Techniques for Automatic Fingerprint Recognition System using Minutiae Extraction | en_US |
| dc.type | Thesis | en_US |