Cover Image

Age Group Estimation from Face Images

Age group estimation is useful in real-world applications such as security access control and human computer interaction. We have proposed an age group estimation algorithm based on the wrinkle features on the face image. During pre-processing stage, geometric normalization is performed to correct t...

Full description

Saved in:
Bibliographic Details
Main Author: Tiong, Pei Kee
Format: Final Year Project / Dissertation / Thesis
Published: 2015
Subjects:
TA Engineering (General). Civil engineering (General)
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://eprints.utar.edu.my/1809/1/Age_Group_Estimation_from_Face_Images.pdf
http://eprints.utar.edu.my/1809/
Tags: Add Tag
No Tags, Be the first to tag this record!
id my-utar-eprints.1809
record_format eprints
spelling my-utar-eprints.18092019-08-15T10:41:53Z Age Group Estimation from Face Images Tiong, Pei Kee TA Engineering (General). Civil engineering (General) TK Electrical engineering. Electronics Nuclear engineering Age group estimation is useful in real-world applications such as security access control and human computer interaction. We have proposed an age group estimation algorithm based on the wrinkle features on the face image. During pre-processing stage, geometric normalization is performed to correct the out-of-plane rotated images. Then, conversion of image to grayscale image is performed, if needed; followed by noise removal using median filtering method. Wrinkle features are extracted from the regions of interest of a normalized image using Canny edge detection for age group estimation. Finally, the images are classified into three age groups: babies/ children, young adults and old adults. The average accuracy of the algorithm is 72.66% for good quality images and 44.92% for poor quality images. 2015-09-22 Final Year Project / Dissertation / Thesis NonPeerReviewed application/pdf http://eprints.utar.edu.my/1809/1/Age_Group_Estimation_from_Face_Images.pdf Tiong, Pei Kee (2015) Age Group Estimation from Face Images. Final Year Project, UTAR. http://eprints.utar.edu.my/1809/
institution Universiti Tunku Abdul Rahman
building UTAR Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tunku Abdul Rahman
content_source UTAR Institutional Repository
url_provider http://eprints.utar.edu.my
topic TA Engineering (General). Civil engineering (General)
TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TA Engineering (General). Civil engineering (General)
TK Electrical engineering. Electronics Nuclear engineering
Tiong, Pei Kee
Age Group Estimation from Face Images
description Age group estimation is useful in real-world applications such as security access control and human computer interaction. We have proposed an age group estimation algorithm based on the wrinkle features on the face image. During pre-processing stage, geometric normalization is performed to correct the out-of-plane rotated images. Then, conversion of image to grayscale image is performed, if needed; followed by noise removal using median filtering method. Wrinkle features are extracted from the regions of interest of a normalized image using Canny edge detection for age group estimation. Finally, the images are classified into three age groups: babies/ children, young adults and old adults. The average accuracy of the algorithm is 72.66% for good quality images and 44.92% for poor quality images.
format Final Year Project / Dissertation / Thesis
author Tiong, Pei Kee
author_facet Tiong, Pei Kee
author_sort Tiong, Pei Kee
title Age Group Estimation from Face Images
title_short Age Group Estimation from Face Images
title_full Age Group Estimation from Face Images
title_fullStr Age Group Estimation from Face Images
title_full_unstemmed Age Group Estimation from Face Images
title_sort age group estimation from face images
publishDate 2015
url http://eprints.utar.edu.my/1809/1/Age_Group_Estimation_from_Face_Images.pdf
http://eprints.utar.edu.my/1809/
_version_ 1646030776862507008
score 13.211869

Similar Items