A face-recognition system using embedded network technology
Face recognition is one of the most difficult tasks in science and engineering, which scientists and engineers have tried to perfect over the years. Most of the conventional face recognition systems have been implemented using computers. On the other hand, recognition systems that use microcontrolle...
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| Main Authors: | , , |
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| Format: | text |
| Language: | English |
| Published: |
Animo Repository
2010
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| Subjects: | |
| Online Access: | https://animorepository.dlsu.edu.ph/etd_bachelors/7452 |
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| Institution: | De La Salle University |
| Language: | English |
| Summary: | Face recognition is one of the most difficult tasks in science and engineering, which scientists and engineers have tried to perfect over the years. Most of the conventional face recognition systems have been implemented using computers. On the other hand, recognition systems that use microcontrollers have only begun its development in the recent years.
This study presents an embedded face recognition system one that uses the Blackfin 537 EZ-Kit Lite microcontroller as the main tool for image data acquisition and processing. The system is implemented such that the capture of images is done using the Blackfin board and a server, connected to the Blackfin board through the Ethernet, receives the captured image and compares it to existing face features, known as Eigenfaces, found within the server's database. |
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