We used mathematical morphology and Otsu method in order to detect shadows in high spatial resolution images depicting urban areas. In such scenarios shadows represent an important drawback when extracting information from the scenes. As study areas we used four regions of a Quickbird red band image with 2,5 m of spatial resolution depicting the urban area of Votuporanga. In the first step of the method we filtered the contrast among regional maxima. The contrast criteria was chosen empirically and applied to all scenes. In the second step a morphological top-hat using morphological area closing was carried out in order to enhance shadow areas. Once again, the area criteria adopted when applying the area closing was defined empirically and remained the same for all experiments. Finally, Otsu's method for image binarization was applied to detect the shadows. We show a visual and a quantitative analysis of the results. The mean accuracy of the detection was 91,08% \ub1 0,81. The small standard deviation reflects the robustness of the method which is fully automated.Pages: 8308-831
