Facial feature extraction
This project presents the facial feature extraction system and face recognition system. The test image that used for this project contain various type. There are ten different images of each of 40 disntinct subjects. For some subjects, the images were taken at different times, varying the lighting,...
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| Format: | Undergraduates Project Papers |
| Language: | English |
| Published: |
2009
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/1961/1/Muhammad_Marzuq_Mohd_Sharip_%28_CD_5310_%29.pdf |
| _version_ | 1825821189334892544 |
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| author | Muhammad Marzuq, Mohd Sharip |
| author_facet | Muhammad Marzuq, Mohd Sharip |
| author_sort | Muhammad Marzuq, Mohd Sharip |
| collection | UMP |
| description | This project presents the facial feature extraction system and face recognition system. The test image that used for this project contain various type. There are ten different images of each of 40 disntinct subjects. For some subjects, the images were taken at different times, varying the lighting, facial expressions; open or closed eyes, smiling or not smiling, and facial details; glasses or no glasses. All the images were taken against a dark homogeneous background with the subjects in an upright, frontal position with tolerance for some side movement. For the facial feature extraction system, it is more focus on eye extraction. The eye will extracted from the face by finding the centroid of the eye region using threshold technique. For the recognition system, Principle Component Analysis (PCA) is used to match the test image with the database image. The system will find which database image has a maximum percentage based on similarity of the pattern of the image |
| first_indexed | 2024-03-06T11:37:47Z |
| format | Undergraduates Project Papers |
| id | UMPir1961 |
| institution | Universiti Malaysia Pahang |
| language | English |
| last_indexed | 2024-03-06T11:37:47Z |
| publishDate | 2009 |
| record_format | dspace |
| spelling | UMPir19612021-06-30T03:08:07Z http://umpir.ump.edu.my/id/eprint/1961/ Facial feature extraction Muhammad Marzuq, Mohd Sharip TK Electrical engineering. Electronics Nuclear engineering This project presents the facial feature extraction system and face recognition system. The test image that used for this project contain various type. There are ten different images of each of 40 disntinct subjects. For some subjects, the images were taken at different times, varying the lighting, facial expressions; open or closed eyes, smiling or not smiling, and facial details; glasses or no glasses. All the images were taken against a dark homogeneous background with the subjects in an upright, frontal position with tolerance for some side movement. For the facial feature extraction system, it is more focus on eye extraction. The eye will extracted from the face by finding the centroid of the eye region using threshold technique. For the recognition system, Principle Component Analysis (PCA) is used to match the test image with the database image. The system will find which database image has a maximum percentage based on similarity of the pattern of the image 2009-12 Undergraduates Project Papers NonPeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/1961/1/Muhammad_Marzuq_Mohd_Sharip_%28_CD_5310_%29.pdf Muhammad Marzuq, Mohd Sharip (2009) Facial feature extraction. Faculty of Electrical & Electronic Engineering, Universiti Malaysia Pahang. |
| spellingShingle | TK Electrical engineering. Electronics Nuclear engineering Muhammad Marzuq, Mohd Sharip Facial feature extraction |
| title | Facial feature extraction |
| title_full | Facial feature extraction |
| title_fullStr | Facial feature extraction |
| title_full_unstemmed | Facial feature extraction |
| title_short | Facial feature extraction |
| title_sort | facial feature extraction |
| topic | TK Electrical engineering. Electronics Nuclear engineering |
| url | http://umpir.ump.edu.my/id/eprint/1961/1/Muhammad_Marzuq_Mohd_Sharip_%28_CD_5310_%29.pdf |
| work_keys_str_mv | AT muhammadmarzuqmohdsharip facialfeatureextraction |