Automatic generation of character groundtruth for scanned documents: a closed-loop approach

Character groundtruth for scanned document images is crucial for evaluating the performance of OCR systems, training OCR algorithms, and validating document degradation models. Unfortunately, manual collection of accurate groundtruth for characters in a real (scanned) document image is not possible because (i) accuracy in delineating groundtruth character bounding boxes is not high enough, (ii) it is extremely laborious and time consuming and (iii) the manual labor required for this task is prohibitively expensive. In this paper we present a closed-loop methodology for collecting very accurate (within a pixel error) groundtruth for scanned documents. We rst create ideal documents using a typesetting language. Next we create the groundtruth for the ideal document. The ideal document is then printed, photocopied and scanned. A registration algorithm estimates the geometric transformation that registers the ideal document image to the scanned document image. Finally, groundtruth associated with the ideal document image is transformed using the estimated geometric transform to create the groundtruth for the scanned document image. This methodology is very general and can be used for creating groundtruth for documents typeset in any language, layout, font, and style. The cost of creating groundtruth using our methodology is minimal. We use this methodology to groundtruth 33 English documents consisting of over 62000 symbols. The procedure takes approximately 5 minutes to groundtruth each page on a SUN Sparc 10. Furthermore, we use the method to groundtruth Hindi and FAX documents without any modiication to our procedure. Our software will be made available to researchers shortly.