FACE PROFILE RECOGNITION AND IDENTIFICATION | ||
| JES. Journal of Engineering Sciences | ||
| Article 8, Volume 39, No 5, September and October 2011, Pages 1043-1054 PDF (225.3 K) | ||
| Document Type: Research Paper | ||
| DOI: 10.21608/jesaun.2011.129383 | ||
| Authors | ||
| Shimaa M. Hani1; Hesham Keshk1; Mohamed El-Adawy1; Tarek El- Tobely2 | ||
| 1Electronics, Communications & Computer Department, Helwan University, Egypt | ||
| 2Computer and Automatic Control Department, Tanta University, Egypt | ||
| Abstract | ||
| Since the early 1990's face Recognition Technology (FRT) became an active research area. Most of the current profile recognition algorithms depend on the correct detection of fiducial points and the determination of relationships among these fiducial points. Unfortunately, some features such as concave nose, lips, flat chin, etc. make detection of such points difficult and unreliable. Also the number and position of fiducial points vary when pose changes even for the same person. In this paper, a curvature-proposed technique is presented, which does not require the extraction of all the fiducial points, but uses information contained in the profile. The nearest neighbor interpolation method is used to smooth the profile and then the curvature of the interpolated profile is computed. Using the curvature coefficient values, the fiducial points, such as nasion, chin, and forehead can be reliably extracted using a fast and simple method. Then an Euclidean distance method is applied to match the face profile based on the curvature coefficient values. Experiments are performed on collected 50 clients with different ages, in public area. Each had three shots differences in time capture and illuminations, getting total of 150 images database, recognition rate of 96.67% and conclusion are presented and discussed. | ||
| Keywords | ||
| face profile; curve fitting; face recognition; human features, curvature; facial extraction, facial motion; facial expression; nasal detection and identification | ||
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