Spectral contrasts for landmark navigation.
Visual robot navigation in outdoor environments would benefit from an illumination-independent representation of images. We explore how such a representation, comprising a black skyline of objects in front of a white sky, can be obtained from dual-channel spectral contrast measures. Light from sky and natural objects under different conditions of illumination was analyzed by five spectral channels: ultraviolet, blue, green, red, and near infrared. Linear discriminant analysis was applied to determine the optimal linear separation between sky and object points. A statistical comparison shows that contrasts with large differences in the wavelength of the two channels, specifically ultraviolet-infrared, blue-infrared, and ultraviolet-red, yield the best separation. Within a single channel, the best separation was obtained for ultraviolet light. The gain in separation quality when all five channels were included is relatively small.
Kollmeier
Thomas
T
Computer Engineering Group, Faculty of Technology, Bielefeld University, Bielefeld, Germany. www.ti-uni-bielefeld.de
Röben
Frank
F
Schenck
Wolfram
W
Möller
Ralf
R
D000465:Algorithms; D001185:Artificial Intelligence; D003116:Color; D003124:Colorimetry / Q000379:methods*; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods; D009038:Motion; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012371:Robotics / Q000379:methods*; D012680:Sensitivity and Specificity; D013057:Spectrum Analysis / Q000379:methods*