Identifying Individuals using Robust Face Recognition Techniques
| dc.contributor.author | Ben Mimouna, Amel | |
| dc.contributor.author | Supervisor: Assas, Ouarda | |
| dc.contributor.author | Supervisor: Benouis, Mohamed | |
| dc.date.accessioned | 2023-05-22T13:27:24Z | |
| dc.date.available | 2023-05-22T13:27:24Z | |
| dc.date.issued | 2015-06-10 | |
| dc.description.abstract | In recent years, there has been a growing interest around biometrics. Facial recognition, as a biometric technology, has played an increasingly important role in the field of research, because of its non-intrusive and contactless. This work is proposed the face recognition method using component analysis(PCA) , linear discriminant analysis(LDA) and local binary pattern(LBP) With measure distance. During testing, In addition, we have introduced the multi biometrics system particularly multi-algorithm and multimodal systems. To improve the performance of the identification system. For the validation of this work, we use database ORL and Yale. Experimental results show that the multimodal fusion scenario (Iris + Face) With the application of LBP and LDA on the iris and face respectively has gives a recognition rate of 98.33% using mean rule of fusion. | en_US |
| dc.identifier.uri | http://dspace.univ-msila.dz:8080//xmlui/handle/123456789/38554 | |
| dc.language.iso | en | en_US |
| dc.publisher | University of M'sila | en_US |
| dc.subject | Face recognition, Iris, Biometrics, PCA, LBP, LDA, Multibiometric, fusion. | en_US |
| dc.title | Identifying Individuals using Robust Face Recognition Techniques | en_US |
| dc.type | Thesis | en_US |