| dc.contributor.author | Mekhilef, Saad, Dr. | |
| dc.contributor.author | S. B., Low | |
| dc.contributor.author | C. L., Ng | |
| dc.contributor.author | M., Mahadani | |
| dc.date.accessioned | 2011-09-13T02:53:32Z | |
| dc.date.available | 2011-09-13T02:53:32Z | |
| dc.date.issued | 2008-06 | |
| dc.identifier.citation | The Journal of the Institution of Engineers, Malaysia, vol. 69(2), 2008, pages 31-39 | en_US |
| dc.identifier.issn | 0126-513X | |
| dc.identifier.uri | http://www.myiem.org.my/content/iem_journal_2008-179.aspx | |
| dc.identifier.uri | http://dspace.unimap.edu.my/123456789/13725 | |
| dc.description | Link to publisher's homepage at http://www.myiem.org.my/ | en_US |
| dc.description.abstract | The paper presents the implementation of algorithms to develop an automatic face recognition system. The system extracts the human face and then recognizing that face for a match of the desired people from face database. It consists of two major phase which are the face detection and face identification. In face detection, the face region is extracted from the original image using skin color techniques. Various techniques are used to handle bad illumination and face alignment problem. In face identification phase, Eigenfaces approach is used to overcome the problems of large sets of image and improper illuminating conditions. Experimental results are presented using images of students. The efficiency of the applied approaches is analyzed and compared with previous works. | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | The Institution of Engineers, Malaysia | en_US |
| dc.subject | Automatic face recognition | en_US |
| dc.subject | Eigenfaces | en_US |
| dc.subject | Face detection | en_US |
| dc.title | Automatic face recognition system | en_US |
| dc.type | Article | en_US |
| dc.contributor.url | saad@um.edu.my | en_US |
