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Automatic Age Prediction of Aging Effects on Face Images

http://hdl.handle.net/20.500.12678/0000004452
47247171-7ae2-4f3f-a3cb-70841b7aff33
b6871112-b771-4c74-9ee3-1f7be4adf822
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10016.pdf 10016.pdf (499 Kb)
Publication type
Article
Upload type
Publication
Title
Title Automatic Age Prediction of Aging Effects on Face Images
Language en_US
Publication date 2012-02-28
Authors
Tin, Hlaing Htake Khaung
Sein, Myint Myint
Description
Automatic age prediction system for grayscale facial images is proposed in this paper. Tenage groups, including, are used in the predictionsystem. The process of the system is divided intothree phases: location, feature extraction, andage prediction. Principal Component Analysis(PCA) was used to reduce dimension andenhance class. Finally Euclidean distance wasused to classify the images into one of sevenmajor groups. These groups are: Group1 (0 to10 years), Group2 (11 to 20 years), Group3 (21to 30 years), Group4 (31 to 40 years), Group5(41 to 50 years), Group6 (51 to 60 years) andGroup7 (60 over). The proposed system isexperimented with 1300 facial images on a Core2 Duo processor with 2 GB RAM. One half of theimages are used for training and the other halffor test. It takes 0.2 second to classify an imageon an average. The identification rate achieves95.5% for the training images and 85.5% for thetest images, which is roughly close to human’ssubjective prediction.
Keywords
Age Prediction, Feature Extraction, Principal component Analysis (PCA)
Identifier http://onlineresource.ucsy.edu.mm/handle/123456789/2383
Journal articles
Tenth International Conference On Computer Applications (ICCA 2012)
Conference papers
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Thesis/dissertations
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