Face recognition implementation using blackfin microprocessor
Date of Publication
2012
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
Leonard U. Ambata
Defense Panel Chair
Edwin Sybingco
Defense Panel Member
Jose Antonio M. Catalan
Alexander C. Abad
Abstract/Summary
This study is all about the development of a stand alone embedded face recognition system to be applied for the security and safety purposes of a small office. The group will work with the Principal Component Analysis (PCA) algorithm which will be implemented in a Blackfin ADSP-BF537 development board. MATLAB and Visual DSP++ were used as the coding environment. The face recognition process begins by capturing the image using the OV07725 image sensor. Raw images will now pass through the Blackfin AV EZ-Extender to get to the development board where the images will be detected and compared to other existing data stored in the board’s flash memory. When as output is reached, data will now be transferred to the LCD for it to be printed. With the system accuracy set of 80%, the boot-up process takes approximately 19 seconds while the face recognition process itself takes only up to three (3) seconds.
Abstract Format
html
Language
English
Format
Accession Number
TU16811
Shelf Location
Archives, The Learning Commons, 12F, Henry Sy Sr. Hall
Recommended Citation
Comia, A. P., Sia, K. G., Tumambing, R. A., & Villarante, C. A. (2012). Face recognition implementation using blackfin microprocessor. Retrieved from https://animorepository.dlsu.edu.ph/etd_bachelors/14794
