Objective Quality Measurement for Geometric Document Image Restoration

Many algorithms to remove distortion from document images have be proposed in recent years, but so far there is no reliable method for comparing their performance. In this paper we propose a collection of methods to measure the quality of such restoration algorithms for document image which show a non-linear distortion due to perspective or page curl. For the result from these measurement to be meaningful, a common data set of ground truth is required. We therefore started with the buildup of a document image database that is meant to serve as a common data basis for all kinds of restoration from images of 3D-shaped document. The long term goal would be to establish this database and following extensions in the area of document image dewarping as an as fruitful and indispensable tool as e.g. the NIST database is for OCR, or the Caltech database is for object and face recognition.