Feature Extraction on Range Images – A New Approach

SA Coleman, BW Scotney, S Suganthan

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Citations (Scopus)


Range images can provide an almost 3-dimensional description of a scene. Feature driven segmentation of range images has been primarily used for 3D object recognition, and hence the accuracy of the detected features is a prominent issue. Feature extraction on range images has proven to be a more complex problem than on intensity images due to both the irregular distribution of range image data and the nature of the features that are present in range images. Approaches to range image feature extraction are often scan line based approximations that carry a significant computational overhead and hence are not appropriate for real-time processing. This paper presents a design procedure for scalable first order derivative operators that can be used directly on irregularly distributed data. Hence the method is appropriate for direct use on range image data without the requirement of image preprocessing and could form the basis of algorithms of real-time robotic applications.
Original languageEnglish
Title of host publicationUnknown Host Publication
PublisherIEEE Robotics and Automation Society
Number of pages6
ISBN (Print)1-4244-0602-1
Publication statusPublished (in print/issue) - Apr 2007
EventIEEE International Conference on Robotics and Automation - Rome
Duration: 1 Apr 2007 → …


ConferenceIEEE International Conference on Robotics and Automation
Period1/04/07 → …


  • range images
  • feature extraction


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