Best Poster Award at ICDAR 2019

At the end of September, the 15th International Conference on Document Analysis and Recognition (ICDAR) took place in Sydney, Australia. We attended this conference with a paper describing the creation of the B-MOD dataset, which was presented here on a poster session. For the poster we received the Best Poster Award.

Help us determine the visual quality of documents

One of the areas we are dealing with is determining the visual quality of a document. This is important, for example, for subsequent adjustment of documents so that the text recognition is as good as possible. Comparing two documents from this perspective using algorithms is very difficult, sometimes impossible. Therefore, we need to manually find out which document looks better. To simplify the work when comparing documents, we created an annotation server. You will see two cut-outs from different documents and the only task is to mark the better-looking one using the button above the image. We would be very happy if you could help us with the comparison and thus improve the text recognition.

Help us improve handwritten text transcription

Systems for automatic handwritten text transcription need training examples from many writers. You have a chance to help us collect such examples and improve transcriptions of historic documents. You can download template pages from our web. We would appreciate if you could print the pages, write the contained text in your own hand and send us the filled pages by mail or scan them and upload the resulting images using our web.