Handwritten Text Recognition

Status: open
Supervisor: Markus Diem, Florian Kleber, Stefan Fiel

Handwritten Text Recognition (HTR) is an open research topic because of the variety of modern, cursive handwriting. The goal – being able to automatically translate handwritten text into machine readable text – is attractive since HTR would render non-digital born documents accessible.

The master thesis will support the READ project which is a EU granted project dedicated to mass digitization of medieval documents from archives and libraries. Within this project, the CVL will develop document analysis methodologies such as form recognition or layout analysis.


A state-of-the-art HTR engine will be implemented and trained. The project aims at learning cutting-edge machine learning methodologies such as Deep Learning or HMMs.


  • Matlab or C++ knowledge
  • Excellent Machine Learning/Computer Vision knowledge