Here you can find an overview of the contents of the lecture in the summer semester 2023. Lecture slides of the introductory lecture 2023.
- The lecture is held in German.
- All documents will be provided electronically in Moodle. A printed lecture script is available in the copy shop from the beginning of the teaching semester.
If you are interested in the lecture in summer semester 2023, please register for it in Moodlefrom March 1th, 2023! You will receive the password or automatically via eMail or on request via eMail to email@example.com. Moodle registration is a prerequisite for online participation.
Responsible / Contact
Target group and requirements
Students of the courses Biomedical Engineering, Computer and Systems Enineering and Computer Science, Media technology, Electrical engineering, Mechanical Engineering / Optronics (see elective module offer in the curriculum). As well students with an interest in image processing as a supplement or to round off their studies.
Good knowledge of physics, mathematics and information and communications technology is helpful.
As well lectures on technical Optics, System Theory, Signals & Systems and highly recommended
Subject of the lecture Basics of Color Image Processing (Image Processing 2) are methods for solving image-based recognition problems in technical systems with color cameras or multi-channel imaging systems. Recognition tasks with camera-based (vision) technical systems are nowadays very common in automation technology, robotics, medical technology, surveillance technology and in the automotive sector.
The course focuses on multi-channel digital images using the example of images of the spectral image modality(color images), which are to be evaluated in terms of concrete tasks. The methods and procedures treated in the lecture are directly derived from known methods of grey scale image processing as treated in the lecture Basics of Image Processing and Pattern Recognition (Image Processing 1) or are newly developed considering the interrelations and the meaning of the colour channels (colour values) of an image. For this purpose, important basics of "colour" as a subjective sensory perception, of colour spaces and systems, of colourimetry are taught in the course and supplemented by knowledge of multispectral measuring and reproducing systems. The aim of image evaluation is the interpretation of the image content at different levels of abstraction. For this purpose, the images must be processed, transformed, converted, analysed and finally classified in the respective technically accessible form, in this case as a multi-channel (colour) image, in order to be able to derive relevant contents and statements. In the course, essential methods, procedures and algorithms are considered and discussed in the context of concrete applications from practice.
The student receives a comprehensive overview of the specifics of processing digital color images in the context of technical recognition tasks. In addition to the purely informatic aspects of image processing, the student is taught important connections to the emergence and technical description of the colour phenomenon and the technical capture in the form of digital colour images. As a result, the student is able to understand and design classical processing chains for solving image-based recognition tasks, to correctly classify and implement partial aspects of processing solutions, and to move conceptually confidently in this interdisciplinary field of knowledge. For the understanding of current application areas in this field, such as multispectral and multimodal image acquisition and image signal processing, important prerequisites are created by the lecture.
Building on the contents taught in the lecture, the student can use the acquired knowledge in further courses of the bachelor and master studies, e.g.
System technology and system theory of image processing
as well as further courses on applied image processing / artificial intelligence at the TU Ilmenau.
The course is accompanied by an exercise in which the lecture contents are reviewed and deepened and simple image processing tasks are worked on with a prototyping software for image processing solutions (VIP-Toolkit). Numerous teaching examples are provided for the lecture.
Introduction / Basics
Important representatives of color science: Newton, Goethe, Grassmann
Color and color perception
Basics of colorimetry
Color spaces and color charts
Approaches to colorimetry and color calibration
Color image processing / processing of multichannel images
Statistics and point operations
Color indexing and histogram matching techniques
Linear and nonlinear methods for noise reduction and edge detection
Selected methods of image analysis for color and multichannel images
Feature extraction and classification
Exercises with VIP Toolkit™-Rapid Prototyping- Student Version.
M. Richter: Einführung in die Farbmetrik. Walter de Gruyter 1981, ISBN 3-11-008209-8.
L. W. MacDonald.: Colour imaging : vision and technology. Wiley, 1999, ISBN 0-471-98531-7.
Koschan, A. and Abidi, M. A.: Digital Color Image Processing. Wiley-Interscience, 2008.
Sangwine, Stephen J.: The colour image processing handbook. Chapman & Hall, 1998, ISBN 0-412-80620-7.
R.C. Gonzalez, R.E. Woods: Digital Image Processing. Addison-Wesley Publishing Company 2007, ISBN 978-0131687288.
as well as the recommended reading for the lecture Basics of Image Processing and Pattern Recognition (Image Processing 1)
P achievements as a prerequisite for module completion through homeworks during the semester (aSL). Module grade from a written exam, 90 minutes or an oral exam (by arrangement).