Research Article
FPGA Implementation of Face Recognition Algorithm
@INPROCEEDINGS{10.1007/978-3-319-74935-8_13, author={Tijana Šušteršič and Aleksandra Vulović and Nenad Filipović and Aleksandar Peulić}, title={FPGA Implementation of Face Recognition Algorithm}, proceedings={Pervasive Computing Paradigms for Mental Health. Selected Papers from MindCare 2016, Fabulous 2016, and IIoT 2015}, proceedings_a={MINDCARE \& IIOT \& FABULOUS}, year={2018}, month={3}, keywords={FPGA Face recognition Eigenface algorithm}, doi={10.1007/978-3-319-74935-8_13} }- Tijana Šušteršič
Aleksandra Vulović
Nenad Filipović
Aleksandar Peulić
Year: 2018
FPGA Implementation of Face Recognition Algorithm
MINDCARE & IIOT & FABULOUS
Springer
DOI: 10.1007/978-3-319-74935-8_13
Abstract
Field of face recognition has been developing in the past several decades. Although percentage of successful recognition algorithms is constantly getting higher, there is room for improvement. Field Programmable Gate Array (FPGA) is technology that can be used for speed and accuracy improvement. The main goal of this paper was to load photos from files to FPGA and display, as well as describe implementation of the Eigenface algorithm on DE2 Altera board. We showed that DE2 Altera board can be used for reading databases and photos from crime scenes and discussed how Eigenface algorithm can be implemented on this board in order to speed up the process of face recognition. Speed of recognition process is an area where improvement is necessary, especially considering the need for instant face recognition in places like airports, or public meetings.
