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A configurable architecture for the generalized hough transform applied to the analysis of huge aerial images and to traffic sign detection

: Kiefer, Gundolf; Vahl, Matthias; Sarcher, Julian; Schäferling, Michael


Athanas, Peter (Ed.) ; Institute of Electrical and Electronics Engineers -IEEE-:
International Conference on ReConFigurable Computing and FPGAs, ReConFig 2016 : Cancun, Mexico, November 30 - December 2, 2016
Piscataway, NJ: IEEE, 2016
ISBN: 978-1-5090-3707-0
ISBN: 978-1-5090-3708-7
7 pp.
International Conference on ReConFigurable Computing and FPGAs (ReConFig) <2016, Cancun>
Conference Paper
Fraunhofer IGD ()
Fraunhofer IGD-R ()
field-programmable gate array (FPGA); object recognition; computer vision; aerial images; detection; Guiding Theme: Digitized Work; Research Area: Computer vision (CV)

Object recognition in huge image data sets or in live camera images at interactive frame rates is a very demanding task, especially within embedded systems. The recognition task includes the localization of a reference object and its rotation and scaling in a search image. The Generalized Hough Transform (GHT) is known as a powerful and robust technique to support this task by transforming the search image into a 4D parameter space. However, the GHT itself is very complex and demanding towards computational power and memory consumption. This paper presents a novel hardware architecture to perform a complete 4D GHT at interactive frame rates in an FPGA. The architecture is configurable in order to allow a trade-off between performance, accuracy and hardware usage. The proposed architecture has been implemented in a low-cost Zynq-7000 FPGA and successfully evaluated in two practical applications, namely groyne detection in aerial images and traffic sign detection.