Document Image Analysis

Document Image Analysis (DIA) is a cross-domain of computer vision and pattern recognition and refers to an established research field dealing with the extraction of any kind of exploitable information from document images. Printed and handwritten text recognition, known as OCR/ICR (Optical/Intelligent Character recognition), is part of the discipline, but represents only one aspect. Other challenging topics include document classification, layout analysis, writer identification/authentication, signature recognition, table recognition, logical structure recognition, etc.

The aim of the Master course is to provide an overview of methods, from basic image processing to machine learning, which are described in the scientific literature to address different steps of DIA; this includes image binarization, page segmentation, graphics/text separation, text bock and text line detection, feature extraction and classification (at various levels). As a practical exercise, students will be asked to do a project (either individually or within a group of max. 4 peoples), which addresses a specific DIA challenge, including potentially the participation to international competitions.

Details

Code 33107
63107
Type Course
ECTS 5
Site Fribourg
Track(s) T3 – Advanced Information Processing
T6 – Data Science
Semester S2021

Teaching

Learning Outcomes
  • get a good overview of the DIA research domain
  • get a deep understanding of the processing chains involved in DIA applications
  • apply a rigorous methodology to design, implement, and evaluate a scientific experiment
Lecturer(s) Rolf Ingold
Language english
Course Page

The course page in ILIAS can be found at https://ilias.unibe.ch/goto_ilias3_unibe_crs_2034264.html.

Schedules and Rooms

Period Weekly
Schedule Tuesday, 14:15 - 17:00
Location UniFR, PER21

Additional information

Comment

First Lecture
The first lecture will take place online on Tuesday, 23.02.2021 at 14:15.