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An estimation approach is proposed in this paper based on the binocular stereovision to collect the degree of crowdedness in public transports. The proposed method combines the disparity with frame differences to extract the foreground object. An adaptive window normalized cross correlation (NCC) matching and interpolated method is applied to get the sub-pixel image disparity value. Then, the foreground object is projected to the horizontal plane to eliminate the influence of the occlusion and perspective effect. Finally the degree of crowdedness is calculated from the area and the perimeter of the foreground objects. Experimental results show that the proposed method can obtain good estimation results in the simulated scenes in the laboratory and on parking or moving buses. This approach is effective to illumination changes, shadows and occlusion of passengers. 相似文献
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The paper studies a technique of container image ID recognition. In the image preprocessing phase, thresholdiong based on
histogram and adaptive thresholding is used. In the character segmentation phase, a labeling method is used, which is based on connected
region, location of character block, location of character line recovery of absent and fragmented characters. In the recognition phase, adaptive
template match and multiple image results synthesis are used. A high recognition rate is obtained. 相似文献
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