U-Net-bin: hacking the document image binarization contest

Computer Optics. – 2019. – Vol. 43(5). – P. 825-832. – DOI: 10.18287/2412-6179-2019-43-5-825-832.

Image binarization is still a challenging task in a variety of applications. In particular, Document Image Binarization Contest (DIBCO) is organized regularly to track the state-of-the-art techniques for the historical document binarization. In this work we present a binarization method that was ranked first in the DIBCO`17 contest. It is a convolutional neural network (CNN) based method which uses U-Net architecture, originally designed for biomedical image segmentation. We describe our approach to training data preparation and contest ground truth examination and provide multiple insights on its construction (so called hacking). It led to more accurate historical document binarization problem statement with respect to the challenges one could face in the open access datasets. A docker container with the final network along with all the supplementary data we used in the training process has been published on Github.


Test Drive Our Smart Engines

Free demo apps allow you to experience the power of Smart Engines software for intelligent document scanning in a real-world context.

Why not experience the power of Smart Engines for yourself? Our demo apps allow you to test the capabilities of our identity document recognition software on mobile devices in videostream or in a single image (photo, scan).

Simply display any document to the camera in real-time or choose a photo from the gallery, and the app will recognize and capture the necessary data.

Demo apps Privacy Policy

id documents enginge by Smart Engines
Apple App Store Badge
Google Play Badge
id documents enginge by Smart Engines

Send Request

Send request for quotation or more information about products.

Contact Form

Smart Engines is to provide a reply within 2 business days. If you don't receive a message from our representative within 2 business days, please check your spam folder or simply send us an email to sales@smartengines.com

Smart Engines is committed to privacy, we are fully compliant with GDPR and CCPA, all the personal data is intended for internal use only.