Extracting points features from laser rangefinder data based on hough transform

Novel Certad, Carlos Mastalli, Jose Cappelletto, Juan C. Grieco

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

Abstract / Description of output

This paper describes a novel feature extraction method for laser rangefinder data. Extracted features correspond to real and virtual corners of the scanned scene. The method is based on the Hough Transform (HT) for line extraction, where the intersecting points of these lines are considered as features. This work highlights the use of the HT outside of image applications, and presents a new filtering algorithm that reduces false positive in line detection by the HT based method. The developed method was tested under various simulated benchmarks in order to compare the performance as a function of correctness, uncertainty, execution time and other parameters. Also, a real data benchmark was included in the tests. Finally, a simulation of EKF-SLAM was performed to demonstrate the functionality of the developed method in more complex tasks.
Original languageEnglish
Title of host publication2014 IEEE ANDESCON
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Number of pages1
ISBN (Electronic)978-1-4799-6686-8
Publication statusPublished - 4 May 2015
EventVII Congreso Internacional de la Región Andina IEEE 2014: IEEE ANDESCON 2014 - Cochabamba, Bolivia, Plurinational State of
Duration: 15 Oct 201417 Oct 2014


ConferenceVII Congreso Internacional de la Región Andina IEEE 2014
Country/TerritoryBolivia, Plurinational State of

Keywords / Materials (for Non-textual outputs)

  • feature extraction
  • Hough transforms
  • Kalman filters
  • laser ranging
  • SLAM (robots)
  • novel feature extraction method
  • laser rangefinder data
  • Hough transform
  • HT based method
  • line extraction
  • filtering algorithm
  • Feature extraction
  • Lasers
  • Transforms
  • Benchmark testing
  • Data mining
  • Uncertainty
  • Simultaneous localization and mapping


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