DocumentCode :
3539657
Title :
Facial image classification based on age and gender
Author :
Kalansuriya, Thakshila R. ; Dharmaratne, Anuja T.
fYear :
2013
fDate :
11-15 Dec. 2013
Firstpage :
44
Lastpage :
50
Abstract :
Automatic face identification and verification from facial images attain good accuracy with large sets of training data while face attribute recognition from facial images still remain challengeable. We propose a methodology for automatic age and gender 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.
Keywords :
face recognition; feature extraction; image classification; image texture; lighting; neural nets; age classification; artificial neural networks; face attribute recognition; face identification; face verification; facial image classification; feature extraction; gender classification; illumination conditions; image classification; image preprocessing; lighting conditions; primary feature; secondary feature; shape variation; texture variation; wrinkles; Accuracy; Classification algorithms; Face; Feature extraction; Image color analysis; Mouth; Nose; Age classification; Feature extraction; Gender classification; Texture; Wrinkles;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advances in ICT for Emerging Regions (ICTer), 2013 International Conference on
Conference_Location :
Colombo
Print_ISBN :
978-1-4799-1275-9
Type :
conf
DOI :
10.1109/ICTer.2013.6761153
Filename :
6761153
Link To Document :
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