| Autor: |
Jamal Ahmad DARGHAM, Ali CHEKIMA, Ervin Gubin MOUNG, Segiru OMATU |
| Jazyk: |
angličtina |
| Rok vydání: |
2018 |
| Předmět: |
|
| Zdroj: |
Advances in Distributed Computing and Artificial Intelligence Journal, Vol 7, Iss 2, Pp 43-52 (2018) |
| Druh dokumentu: |
article |
| ISSN: |
2255-2863 |
| DOI: |
10.14201/ADCAIJ2018724352 |
| Popis: |
Face recognition is an important biometric method because of its potential applications in many fields, such as access control and surveillance. In this paper, the performance of the individual channels from the YCBCR colour space on face recognition for surveillance applications is investigated and compared with the performance of the grayscale. In addition, the performance of fusing two or more colour channels is also compared with that of the grayscale. Three cases with a different number of training images per persons were used as a test bed. It was found out that, the grayscale always outperforms the individual channel. However, the fusion of CBxCR with any other channel outperforms the grayscale when three images of the same class from the same database are used for training. Regardless of the cases used, the CBxCR channel always gave the best performance for the individual colour channels. It was found that, in general, increasing the number of fused channels increases the performance of the system. It was also found that the grayscale channel is the better choice for face recognition since it contains better quality edges and visual features which are essential for face recognition. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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