Naji, Sinan and Zainuddin, Roziati and A. Jallb, Hamid and Zaid, Masoud Abou and Eldouber, Amar (2011) Neural network-based face detection with partial face pattern. In: International Arab Conference on Information Technology, 11-14 Dec 2011, Riyadh, Arab Saudi.
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Abstract
In this paper, we present a neural networkbased method to detect frontal faces in grayscale images under unconstrained scene conditions such as the presence of complex background and uncontrolled illumination. The system is composed of two stages: threshold-based segmentation and neural network-based classifier. Image segmentation using thresholding is used to reduce the search space. Artificial neural network classifier would then be applied only to regions of the image which are marked as candidate face regions. The ANN classification phase crops small windows of an image, and decides whether each window contains a face. Partial face template is used instead of the whole face to make training process easier. To minimize the probability of misrecognition, texture descriptors such as mean, standard deviation, smoothness and X-Y-Relieves are measured and entered besides the image as input data to form solid feature vector. The ANN training phase is designed to be general with minimum customization and to output the presence or absence of a face (i.e. face or non-face). In this work, partial face template is used instead of the whole face. Aligning faces is done using only one point that is “face center”.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Funders: | UNSPECIFIED |
| Uncontrolled Keywords: | Thresholding; Image segmentation; Artificial neural network; Texture analysis; Face detection |
| Subjects: | T Technology > T Technology (General) |
| Divisions: | Faculty of Computer Science & Information Technology |
| Depositing User: | Mr. Mohd Samsul Ismail |
| Date Deposited: | 09 Mar 2015 01:03 |
| Last Modified: | 09 Oct 2018 07:24 |
| URI: | http://eprints.um.edu.my/id/eprint/12911 |
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