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.

Objectives

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.

Requirements

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