Shadows often incur uneven illumination to pavement images, which brings great challenges to image-based pavement crack detection. Thus, it is desired to remove pavement shadows before detecting pavement cracks. However, due to the large penumbras cast by trees, light poles, etc., it is difficult to locate shadows in a pavement image. In this paper, an automatic pavement shadow removal method is proposed based on geodesic analysis. First, a geodesic shadow model is used to partition a pavement shadow into a number of geodesic regions. Then, an optimal background region is selected for reference by statistic analysis. Finally, a texture-balanced illuminance compensation is applied on all geodesic regions over the image. Experiments demonstrate the effectiveness of the proposed method.
['Qin Zou', 'Zhongwen Hu', 'Long Chen', 'Qian Wang', 'Qingquan Li']
Geodesic-based pavement shadow removal revisited