Road sign recognition system on Raspberry Pi

Enis Bilgin, Stefan Robila

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations

Abstract

Digital image processing, i.e. the use of computer systems to process pictures, has applications in many fields, including of medicine, space exploration, geology and oceanography and continues to increase in its applicability. The main objective of this paper is to demonstrate the ability of image processing algorithms on a small computing platform. Specifically we created a road sign recognition system based on an embedded system that reads and recognizes speed signs. The paper describes the characteristics of speed signs, requirements and difficulties behind implementing a real-time base system with embedded system, and how to deal with numbers using image processing techniques based on shape and dimension analysis. The paper also shows the techniques used for classification and recognition. Color analysis also plays a specifically important role in many other different applications for road sign detection, this paper points to many problems regarding stability of color detection due to daylight conditions, so absence of color model can led a better solution. In this project lightweight techniques were mainly used due to limitation of real- time based application and Raspberry Pi capabilities. Raspberry Pi is the main target for the implementation, as it provides an interface between sensors, database, and image processing results, while also performing functions to manipulate peripheral units (usb dongle, keyboard etc.).

Original languageEnglish
Title of host publication2016 IEEE Long Island Systems, Applications and Technology Conference, LISAT 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781467384902
DOIs
StatePublished - 16 Jun 2016
EventIEEE Long Island Systems, Applications and Technology Conference, LISAT 2016 - Farmingdale, United States
Duration: 29 Apr 2016 → …

Other

OtherIEEE Long Island Systems, Applications and Technology Conference, LISAT 2016
CountryUnited States
CityFarmingdale
Period29/04/16 → …

    Fingerprint

Keywords

  • Digital Image Processing
  • Embedded System
  • Raspberry Pi
  • Road Sign Recognition

Cite this

Bilgin, E., & Robila, S. (2016). Road sign recognition system on Raspberry Pi. In 2016 IEEE Long Island Systems, Applications and Technology Conference, LISAT 2016 [7494102] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/LISAT.2016.7494102