Universität Wien

160167 UE Image processing for the humanities (2023S)

5.00 ECTS (2.00 SWS), SPL 16 - Musikwissenschaft und Sprachwissenschaft
Continuous assessment of course work
Moodle

Registration/Deregistration

Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).

Details

max. 30 participants
Language: English

Lecturers

Classes (iCal) - next class is marked with N

  • Friday 03.03. 16:45 - 18:15 Seminarraum 7 Hauptgebäude, Tiefparterre Stiege 9 Hof 5
  • Friday 10.03. 16:45 - 18:15 Seminarraum 7 Hauptgebäude, Tiefparterre Stiege 9 Hof 5
  • Friday 17.03. 16:45 - 18:15 Seminarraum 7 Hauptgebäude, Tiefparterre Stiege 9 Hof 5
  • Friday 24.03. 16:45 - 18:15 Seminarraum 7 Hauptgebäude, Tiefparterre Stiege 9 Hof 5
  • Friday 31.03. 16:45 - 18:15 Seminarraum 7 Hauptgebäude, Tiefparterre Stiege 9 Hof 5
  • Friday 21.04. 16:45 - 18:15 Seminarraum 7 Hauptgebäude, Tiefparterre Stiege 9 Hof 5
  • Friday 28.04. 16:45 - 18:15 Seminarraum 7 Hauptgebäude, Tiefparterre Stiege 9 Hof 5
  • Friday 05.05. 16:45 - 18:15 Seminarraum 7 Hauptgebäude, Tiefparterre Stiege 9 Hof 5
  • Friday 12.05. 16:45 - 18:15 Seminarraum 7 Hauptgebäude, Tiefparterre Stiege 9 Hof 5
  • Friday 19.05. 16:45 - 18:15 Seminarraum 7 Hauptgebäude, Tiefparterre Stiege 9 Hof 5
  • Friday 26.05. 16:45 - 18:15 Seminarraum 7 Hauptgebäude, Tiefparterre Stiege 9 Hof 5
  • Friday 02.06. 16:45 - 18:15 Seminarraum 7 Hauptgebäude, Tiefparterre Stiege 9 Hof 5
  • Friday 09.06. 16:45 - 18:15 Seminarraum 7 Hauptgebäude, Tiefparterre Stiege 9 Hof 5
  • Friday 16.06. 16:45 - 18:15 Seminarraum 7 Hauptgebäude, Tiefparterre Stiege 9 Hof 5
  • Friday 23.06. 16:45 - 18:15 Seminarraum 7 Hauptgebäude, Tiefparterre Stiege 9 Hof 5
  • Friday 30.06. 16:45 - 18:15 Seminarraum 7 Hauptgebäude, Tiefparterre Stiege 9 Hof 5

Information

Aims, contents and method of the course

If your research in humanities involves a large amount of image data, whether manuscripts, archival material, or photographs taken on a field trip, you know that the most trivial processing step will become a torture, if applied manually on the 264th image. This course provides an introduction to the methods and procedures that could be useful for dealing with large-quantity image data.

The course focuses on batch editing of images. To achieve this, we need to understand the nature of bitmaps, identify basic image editing operations, and run them automatically on the whole collection of image data. Apart from image editing, we will also learn to apply different algorithms and packages into an image-centered workflow. Common examples are visualization, OCR and image classification, but students with domain-specific needs will receive guidance on these possibilities.

Everything will be done on Python and JupyterLab, with Wand the main package used for batch editing. Students are assumed to have acquired a previous knowledge of Python and JupyterLab, for example, through UE Introduction to DH Tools and Methods. They must bring their own computational environment to the classroom – a laptop, a tablet, or anything with JupyterLab installed and running.

Assessment and permitted materials

Course evaluation will be a combination of in-class participation (30%), eight homework assignments in image editing (40%), and the final project involving both image editing and other processing / extraction methods (30%).

Minimum requirements and assessment criteria

Attendance; assignments must be submitted on time and achieve the requirements; the final project should demonstrate students' ability in the skills learnt in this course.

Examination topics

Theory and practice of image editing, programming ability oriented towards batch automation and the ability to integrate image-oriented algorithms in an automated workflow.

Reading list

To be announced.

Association in the course directory

MA DH: DH Skills II; S-DH Cluster 1, 2, 3 & 4
BA Sprachwissenschaft: Alternative Erweiterung

Last modified: Tu 14.03.2023 11:29