Course­ Manual BV3

Project Image Processing / Pattern Recognition


PDF Course Catalog Deutsche Version: BV3

Version: 1 | Last Change: 16.09.2019 10:19 | Draft: 0 | Status: vom verantwortlichen Dozent freigegeben

Long name Project Image Processing / Pattern Recognition
Approving CModule BV3_BaMT
Responsible
Prof. Dr. Dietmar Kunz
Professor Fakultät IME im Ruhestand
Valid from summer semester 2023
Level Bachelor
Semester in the year summer semester
Duration Semester
Hours in self-study 162
ECTS 6
Professors
Prof. Dr. Dietmar Kunz
Professor Fakultät IME im Ruhestand

Prof. Dr. Lothar Thieling
Professor Fakultät IME
Requirements Module Image Processing
Module Pattern Recognition
Language English
Separate final exam No
Literature
Burger/Burge: Digitale Bildverarbeitung
Gonzales/Woods: Digital Image Processing

Learning goals
Goal type Description
Knowledge problem specific methods resulting from system model and literature search
Skills skilled use of software development environment
Skills skilled use of tools for image processing and image analysis
Skills if required: skilled use of tools for training neural networks
Skills understanding of scientific texts in English
Skills presentation of project results in English
Skills accomplish complex tasks in teams
Skills present project results
Skills Derive complex problem solutions that can be implemented using image processing and image analysis
analyse and understand complex problems
derive system behaviour from specifying texts
analyse systems
model system from subsystems
model, implement, and test subsystems
map subsystems as far as possible on available components (image processing modules), i.e. selection of models and parameters
implement and test required but not available image processing modules in C or Java using software development environment
implement, test, and validate entire system (problem solution)
Derive problem solution as chain of algorithms using image processing modules
parametrize image processing modules
test and validate solution
iteratively improve algorithmic chain
Expenditure classroom teaching
Type Attendance (h/Wk.)
Project 1
Tutorial (voluntary) 0
Special requirements
none
Accompanying material development environment for image processing and image analysis (ImageJ, IBV-Studio), electronic collection of sample programs and sample applications, electronic development environmentfor dreation and training of neural networks
Separate exam Yes
Separate exam
Exam Type EN Projektaufgabe im Team bearbeiten (z.B. im Praktikum)
Details Presenation and documentation of project progress including oral project presentation at mile stone meetings.
Final report.
Minimum standard Project has to be processed with adequate effort and the achieved results must be visible from the presentations and documentation.

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