Performance Evaluation of Curled Textlines Segmentation Algorithms on CBDAR 2007 Dewarping Contest Dataset

Syed Saqib Bukhari, Faisal Shafait, Thomas Breuel

In: IEEE International Conference on Image Processing. IEEE International Conference on Image Processing (ICIP) January 25 Hong Kong IEEE 2010.


Camera-captured document images often contain curled textlines because of geometric and perspective distortions. Finding curled textlines, which is more difficult than straight textline detection, is a primary step in the processing of hand-held camera-captured document images. Detected textlines results can be used for dewarping of warped images, layout-analysis, etc. In this paper, we compare previously reported curled textline segmentation techniques by using the publicly available CBDAR 2007 dewarping contest dataset and vectorial performance evaluation metrics.

Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence