bibtype L - Prototype, methodology, f. module, software
ARLID 0507783
utime 20240103222437.7
mtime 20190823235959.9
title (primary) (eng) Live Canny Edge Detection
publisher
pub_time 2018
keyword video processing
keyword HW acceleration
keyword Zynq
keyword SDSoC
author (primary)
ARLID cav_un_auth*0101179
name1 Pohl
name2 Zdeněk
full_dept (cz) Zpracování signálů
full_dept (eng) Department of Signal Processing
department (cz) ZS
department (eng) ZS
institution UTIA-B
full_dept Department of Signal Processing
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
author
ARLID cav_un_auth*0225749
name1 Kohout
name2 Lukáš
full_dept (cz) Zpracování signálů
full_dept Department of Signal Processing
department (cz) ZS
department ZS
institution UTIA-B
full_dept Department of Signal Processing
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
author
ARLID cav_un_auth*0101120
name1 Kadlec
name2 Jiří
full_dept (cz) Zpracování signálů
full_dept Department of Signal Processing
department (cz) ZS
department ZS
institution UTIA-B
full_dept Department of Signal Processing
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
source
url http://sp.utia.cz/index.php?ids=results&id=canny
cas_special
project
ARLID cav_un_auth*0374054
project_id 8A18013
agency GA MŠk
abstract (eng) This demo shows Live Canny Edge detection implemented on Trenz Zynq Ultrascale+ TE0808 and TEBF0808 Carrier assembly. The design is based on Trenz SKHio_zusys_SDSoC package downloadable from Trenz web pages. It provides basic HDMI in/out chain for Avnet FMC Imageon extension card. Sources for Canny edge detection filter are available free in xfOpenCV library. The xfOpenCV is Xilinx library of OpenCV cores rewritten to be synthesizable by Vivado HLS tool. The library provides one example for each supported function including Canny edge detector. Each example reads input from file(s) and writes output file with result. The result is also compared with original OpenCV function used as golden model.
RIV JC
FORD0 20000
FORD1 20200
FORD2 20206
reportyear 2020
num_of_auth 3
inst_support RVO:67985556
permalink http://hdl.handle.net/11104/0298853
confidential S
arlyear 2018
mrcbU10 2018