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...
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| Format: | Final Year Project / Dissertation / Thesis |
| Published: |
2015
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| Online Access: | http://eprints.utar.edu.my/1809/1/Age_Group_Estimation_from_Face_Images.pdf http://eprints.utar.edu.my/1809/ |
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| _version_ | 1833428012415057920 |
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| author | Tiong, Pei Kee |
| author_facet | Tiong, Pei Kee |
| author_sort | Tiong, Pei Kee |
| building | UTAR Library |
| collection | Institutional Repository |
| content_provider | Universiti Tunku Abdul Rahman |
| content_source | UTAR Institutional Repository |
| continent | Asia |
| country | Malaysia |
| 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 |
| id | my-utar-eprints.1809 |
| institution | Universiti Tunku Abdul Rahman |
| publishDate | 2015 |
| 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/ |
| spellingShingle | TA Engineering (General). Civil engineering (General) TK Electrical engineering. Electronics Nuclear engineering Tiong, Pei Kee Age Group Estimation from Face Images |
| title | 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_short | Age Group Estimation from Face Images |
| title_sort | age group estimation from face images |
| topic | TA Engineering (General). Civil engineering (General) TK Electrical engineering. Electronics Nuclear engineering |
| url | http://eprints.utar.edu.my/1809/1/Age_Group_Estimation_from_Face_Images.pdf http://eprints.utar.edu.my/1809/ |
| url_provider | http://eprints.utar.edu.my |