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The Scientific World Journal
Volume 2014, Article ID 879031, 16 pages
Research Article

A Modified Active Appearance Model Based on an Adaptive Artificial Bee Colony

1Pattern Recognition Research Group, Centre for Artificial Intelligence Technology, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia, 43600 Bandar Baru Bangi, Malaysia
2Department of Computer Science, Faculty of Education for Women, University of Kufa, Iraq
3Data Mining and Optimization Group, Faculty of Information System and Technology, Universiti Kebangsaan Malaysia, 43600 Bandar Baru Bangi, Malaysia

Received 11 February 2014; Accepted 12 July 2014; Published 6 August 2014

Academic Editor: Patricia Melin

Copyright © 2014 Mohammed Hasan Abdulameer et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Active appearance model (AAM) is one of the most popular model-based approaches that have been extensively used to extract features by highly accurate modeling of human faces under various physical and environmental circumstances. However, in such active appearance model, fitting the model with original image is a challenging task. State of the art shows that optimization method is applicable to resolve this problem. However, another common problem is applying optimization. Hence, in this paper we propose an AAM based face recognition technique, which is capable of resolving the fitting problem of AAM by introducing a new adaptive ABC algorithm. The adaptation increases the efficiency of fitting as against the conventional ABC algorithm. We have used three datasets: CASIA dataset, property 2.5D face dataset, and UBIRIS v1 images dataset in our experiments. The results have revealed that the proposed face recognition technique has performed effectively, in terms of accuracy of face recognition.