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

Print

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)

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