Truthing for Pixel-Accurate Segmentation

We discuss problems in developing policies for ground truthing document images for pixel-accurate segmentation. First, we describe ground truthing policies that apply to four different scales: (1) paragraph, (2) text line, (3) character, and (4) pixel. We then analyze difficult and/or ambiguous cases that will challenge any policy, e.g. blank space, overlapping content, etc. Experiments have shown the benefit of using "tighter\´\´ zones that capture more detail (e.g., at the text line level, instead of paragraph). We show that tighter ground truth does significantly improve classification results, by 45% in recent experiments. It is important to face the fact that a pixel-accurate segmentation can be better than manually obtained ground truth. In practice, perfectly accurate pixel-level ground truth may not be achievable of course, but we believe it is important to explore methods to semi-automatically improve existing ground truth.