Abstract
Automatic face identification and verification from facial images attain good accuracy with large sets of training datawhile face attribute recognition from facial images still remainchallengeable. We propose a methodology for automatic age andLKgender classification based on feature extraction from facial, images, namely, primary and secondary features. Our methodology · includes three main iterations: Preprocessing, Feature extraction and Classification. Our solution is able to classify images in different lighting conditions and different illumination conditions. Classification is done using Artificial Neural Networks according to the different shape and texture variations of wrinkles on face images.
Original language | English |
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Title of host publication | 2013 International Conference on Advances in ICT for Emerging Regions |
Pages | 44-50 |
Number of pages | 7 |
DOIs | |
Publication status | Published - 2013 |
Externally published | Yes |
Event | International Conference on Advances in ICT for Emerging Regions 2013 - Colombo, Sri Lanka Duration: 11 Dec 2013 → 15 Dec 2013 Conference number: 14th https://ieeexplore.ieee.org/xpl/conhome/6747516/proceeding (Proceedings) |
Conference
Conference | International Conference on Advances in ICT for Emerging Regions 2013 |
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Abbreviated title | ICTer 2013 |
Country/Territory | Sri Lanka |
City | Colombo |
Period | 11/12/13 → 15/12/13 |
Internet address |
Keywords
- Age classification
- Feature extraction
- Gender classification
- Texture
- Wrinkles