Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
378356 | Cognitive Systems Research | 2016 | 13 Pages |
Abstract
In this paper a novel method based on facial skin aging features and Artificial Neural Network (ANN) is proposed to classify the human face images into four age groups. The facial skin aging features are extracted by using Local Gabor Binary Pattern Histogram (LGBPH) and wrinkle analysis. The ANN classifier is designed by using two layer feedforward backpropagation neural networks. The proposed age classification framework is trained and tested with face images from PAL face database and shown considerable improvement in the age classification accuracy up to 94.17% and 93.75% for male and female respectively.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Jayant Jagtap, Manesh Kokare,