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.

[1]  H. Opower Multiple view geometry in computer vision , 2002 .

[2]  Jiri Matas,et al.  Robust wide-baseline stereo from maximally stable extremal regions , 2004, Image Vis. Comput..

[3]  Stepán Obdrzálek,et al.  Local affine frames for wide-baseline stereo , 2002, Object recognition supported by user interaction for service robots.

[4]  Per-Erik Forssén,et al.  Maximally Stable Colour Regions for Recognition and Matching , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

[5]  David G. Lowe,et al.  Shape Descriptors for Maximally Stable Extremal Regions , 2007, 2007 IEEE 11th International Conference on Computer Vision.

[6]  David H. Douglas,et al.  ALGORITHMS FOR THE REDUCTION OF THE NUMBER OF POINTS REQUIRED TO REPRESENT A DIGITIZED LINE OR ITS CARICATURE , 1973 .