Detecting Scene Elements Using Maximally Stable Colour Regions
Image processing for autonomous robots is nowadays very popular. In our paper, we show a method how to extract information from a camera attached on a robot to acquire locations of targets the robot is looking for. We apply maximally stable colour regions (a method originally used for image matching) to obtain an initial set of candidate regions. This set is then filtered using application specific filters to find only the regions that correspond to scene elements of interest. The presented method has been applied in practice and performs well even under varying illumination conditions since it does not rely heavily on manually specified colour thresholds. Furthermore, no colour calibration is needed.
KeywordsAutonomous robot Maximally Stable Colour Regions
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- 1.Matas, J., Chum, O., Urban, M., Pajdla, T.: Robust wide baseline stereo from maximally stable extremal regions. In: Proceedings of the British Machine Vision Conference 2002 (BMVC’02), pp. 384–393 (2002)Google Scholar
- 2.Forssén, P.-E.: Maximally stable colour regions for recognition and matching. In: IEEE Conference on Computer Vision and Pattern Recognition, CVPR’07 (2007)Google Scholar
- 3.Matas, J., Obdrzalek, S., Chum, O.: Local affine frames for wide-baseline stereo. In: Proceedings of the 16th International Conference on Pattern Recognition, ICPR’02 (2002)Google Scholar
- 4.Forssén, P.E., Lowe, D.: Shape descriptors for maximally stable extremal regions. In: IEEE International Conference on Computer Vision, ICCV’07 (2007)Google Scholar
- 7.Eurobot: Eurobot autonomous robot contest (2009), http://www.eurobot.org