Title :
OpenCV based road sign recognition on Zynq
Author :
Russell, Matthew ; Fischaber, Scott
Author_Institution :
Analytics Engines, Belfast, UK
Abstract :
Road sign recognition is a key component in autonomous vehicles and also has applications in driver assistance systems and road sign maintenance. Here an algorithm is presented using the Xilinx Zynq-7020 chip on a Zedboard to scan 1920×1080 images taken by an ON Semiconductor VITA-2000 sensor attached via the FMC slot. The PL section of the Zynq is used to perform essential image pre-processing functions and color based filtering of the image. Software classifies the shapes in the filtered image, and OpenCV´s template matching function is used to identify the signs from a database of UK road signs. The system was designed in six weeks, and can process one frame in approximately 5 seconds. This is a promising start for a real-time System on Chip based approach to the problem of road sign recognition and also for using the Zynq platform for rapid deployment of these types of applications.
Keywords :
filtering theory; image classification; image colour analysis; public domain software; road vehicles; system-on-chip; traffic engineering computing; FMC slot; OpenCV-based road sign recognition; UK road sign database; Xilinx Zynq-7020 chip; Zedboard; Zynq PL section; autonomous vehicles; color-based image filtering; driver assistance systems; filtered image shape classification; image preprocessing functions; image scanning; on-semiconductor VITA-2000 sensor; real-time system-on-chip-based approach; road sign identification; road sign maintenance; template matching function; Field programmable gate arrays; Hardware; Image color analysis; Image segmentation; Roads; Shape; Software;
Conference_Titel :
Industrial Informatics (INDIN), 2013 11th IEEE International Conference on
Conference_Location :
Bochum
DOI :
10.1109/INDIN.2013.6622951
