A face-recognition system using embedded network technology
Date of Publication
2010
Document Type
Bachelor's Thesis
Degree Name
Bachelor of Science in Electronics and Communications Engineering
College
Gokongwei College of Engineering
Department/Unit
Electronics and Communications Engineering
Thesis Adviser
Edwin Sybingco
Defense Panel Chair
Enrique M. Manzano
Defense Panel Member
Jingel A. Tio
Noriel C. Mallari
Abstract/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.
Abstract Format
html
Language
English
Format
Accession Number
TU15533
Shelf Location
Archives, The Learning Commons, 12F, Henry Sy Sr. Hall
Physical Description
xiv, 181, [295] leaves ; 28 cm.
Keywords
Image processing--Digital techniques; Human face recognition (Computer science)
Recommended Citation
Ko, R. G., Mandy, C. T., & Tolentino, A. F. (2010). A face-recognition system using embedded network technology. Retrieved from https://animorepository.dlsu.edu.ph/etd_bachelors/7452