Robust Page Segmentation Based on Smearing and Error Correction Unifying Top-down and Bottom-up Approaches
In this paper we present a robust multi-pass page segmentation algorithm. The first pass uses a modified smearing algorithm and the second pass performs a hybrid of bottom-up and top-down segmentation on the output of the first pass. Unlike traditional approaches, the bottom-up and top-down steps are based on primitive results of a smearing based page segmentation algorithm. Therefore, "split" and "merge" processes start with text blocks that are mostly true text blocks but a few of them are either touching or broken. We present experimental results on newspaper and journal documents from different languages to demonstrate the robustness and language independence of our approach.
Citation:
Huaigu Cao, Rohit Prasad, Prem Natarajan, Ehry MacRostie, "Robust Page Segmentation Based on Smearing and Error Correction Unifying Top-down and Bottom-up Approaches," icdar,pp.392-396, Ninth International Conference on Document Analysis and Recognition (ICDAR 2007) Vol 1, 2007