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Title: ISA: Image Synthesis and Analysis
Short Code: MTE7901
ECTS Credits: 2
Organizer Details: BFH HuCE
Evaluation: Final exam 2 weeks after the last course session. The lecture will provide additional information at the beginning of the course.
Decision Date: 23 August 2022 
Start Date: 23 September 2022 
End Date: 11 November 2022 
Date Details:

SW Date CW Morning (4L) Afternoon (4L)
1 23.09.22 38 ISA ISA
2 30.09.2022 39 Self-study
3 07.10.22 40 ISA ISA
5 21.10.22 42 ISA ISA
7 04.11.22 44 ISA ISA
8 11.11.22 45 Self-study Exam ISA


Full day course at 6 Fridays per semester + 1.5 days individual preparation for the exam.


English by default, but deviations according to the wishes of the students.

Description (max. 300 characters): This course is part of the HuCE EVA course series. The course topics are Image Synthesis and Image Analysis.
Contents and Learning Objectives:

Image Analysis (Prof. Marcus Hudritsch)

This course block gives a broader insight into digital image analysis. After a short wrap-up over image processing, we start with the classic feature engineering approach where the software engineer first segments an image into desired regions and represents them in processable data structures. After that, we learn different methods to extract meaningful and discriminative features that we can use in the final step to classify the image. The course block closes with machine learning for image analysis where we learn how to use unsupervised and supervise learning with large labeled datasets to classify images.

Image Synthesis (Prof. Marcus Hudritsch)

This course provides an introduction into modern GPU programming using the OpenGL GLSL Shading Language. We thereby get to know the basic principles of computer graphics. In particular we look at the working of the graphics rendering pipeline and its processing steps like vertex and geometry shader, hidden surface removal, rasterization, fragment processing and depth buffering. Several demo applications and small programming exercises will provide the participants a hands-on knowledge of tools and the GLSL language. The course evaluation will be based on a small, student defined and implemented project and its short presentation.

Admission: Write an E-Mail to : with CC to EVA contact person. Students who are not enrolled at BFH must first register with IS-A:!formInscrs.connection?ww_c_formulaire=FORMULAIRE_ERASMUS

50% theory and 50% labs


Prof. Marcus Hudritsch

Contact Person E-Mail:
Status: finished
Specialization: Industrial Technologies (InT)

Computer Science (CS)

Data Science (DS)

Electrical Engineering (ElE)

Mechatronics & Automation (MA)

Medical Engineering (Med)


[Responsible for this text: Hudritsch Marcus]