论文标题
通过轮廓和对比度检测文档的方法
Approach for Document Detection by Contours and Contrasts
论文作者
论文摘要
本文考虑了在移动设备上执行的任意文档检测。基于经典轮廓的方法通常在遮挡，复杂背景或模糊的情况下失败。基于区域的方法依赖于对象和背景之间的对比，但没有应用程序局限性，但是，其已知的实现极高的资源消耗。我们提出了基于轮廓的方法的修改，其中竞争轮廓位置假设根据边界内部和外部区域之间的对比度进行排名。在实验中，这种修改允许替代排序误差的减少40％，并使整体检测误差减少10％。所提出的方法在Open MIDV-500数据集中提供了无与伦比的最先进性能，并且它证明了与SmartDoc数据集中最先进的性能相当的结果。
This paper considers arbitrary document detection performed on a mobile device. The classical contour-based approach often fails in cases featuring occlusion, complex background, or blur. The region-based approach, which relies on the contrast between object and background, does not have application limitations, however, its known implementations are highly resource-consuming. We propose a modification of the contour-based method, in which the competing contour location hypotheses are ranked according to the contrast between the areas inside and outside the border. In the experiments, such modification allows for the decrease of alternatives ordering errors by 40% and the decrease of the overall detection errors by 10%. The proposed method provides unmatched state-of-the-art performance on the open MIDV-500 dataset, and it demonstrates results comparable with state-of-the-art performance on the SmartDoc dataset.
