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: Ko, Robbie Lloyd G., Mandy, Charlemagne T., Tolentino, Allan Joseph F.
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Language:English
Published: Animo Repository 2010
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Online Access:https://animorepository.dlsu.edu.ph/etd_bachelors/7452
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Institution: De La Salle University
Language: English
id oai:animorepository.dlsu.edu.ph:etd_bachelors-8097
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spelling oai:animorepository.dlsu.edu.ph:etd_bachelors-80972021-07-29T01:42:43Z A face-recognition system using embedded network technology Ko, Robbie Lloyd G. Mandy, Charlemagne T. Tolentino, Allan Joseph F. 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. 2010-01-01T08:00:00Z text https://animorepository.dlsu.edu.ph/etd_bachelors/7452 Bachelor's Theses English Animo Repository Image processing--Digital techniques Human face recognition (Computer science)
institution De La Salle University
building De La Salle University Library
continent Asia
country Philippines
Philippines
content_provider De La Salle University Library
collection DLSU Institutional Repository
language English
topic Image processing--Digital techniques
Human face recognition (Computer science)
spellingShingle Image processing--Digital techniques
Human face recognition (Computer science)
Ko, Robbie Lloyd G.
Mandy, Charlemagne T.
Tolentino, Allan Joseph F.
A face-recognition system using embedded network technology
description 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.
format text
author Ko, Robbie Lloyd G.
Mandy, Charlemagne T.
Tolentino, Allan Joseph F.
author_facet Ko, Robbie Lloyd G.
Mandy, Charlemagne T.
Tolentino, Allan Joseph F.
author_sort Ko, Robbie Lloyd G.
title A face-recognition system using embedded network technology
title_short A face-recognition system using embedded network technology
title_full A face-recognition system using embedded network technology
title_fullStr A face-recognition system using embedded network technology
title_full_unstemmed A face-recognition system using embedded network technology
title_sort face-recognition system using embedded network technology
publisher Animo Repository
publishDate 2010
url https://animorepository.dlsu.edu.ph/etd_bachelors/7452
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