Course code |
02 65 5824 00 |
Number of ECTS points |
5 |
Course title in the language of instruction |
Image Processing and Computer Graphics |
Course title in Polish |
Image Processing and Computer Graphics (Przetwarzanie obrazów i grafika komputerowa) |
Course title in English |
Image Processing and Computer Graphics |
Language of instruction |
English |
Type of classes |
|
Lecture |
Tutorials |
Laboratory |
Project |
Seminar |
Other |
Total of teaching hours during semester |
Contact hours |
30 |
|
15 |
15 |
|
0 |
60 |
E-learning |
No |
No |
No |
No |
No |
No |
|
Assessment criteria (weightage) |
0.50 |
|
0.25 |
0.25 |
|
0.00 |
|
|
Unit running the course |
Instytut Elektroniki |
Course coordinator |
dr hab. inż. Piotr Szczypiński |
Course instructors |
dr inż. Artur Klepaczko, dr hab. inż. Piotr Szczypiński |
Prerequisites |
Understand and be able to apply the tools of linear algebra, particularly matrix calculus, Boolean algebra and matrix calculus. Understanding and ability to program in Python at a functional level, using data structures, loops and conditional statements. |
Course learning outcomes |
- Zgodne z przypisaniem w programie studiów
|
Programme learning outcomes |
- The student knows and understands the basic problems and directions of civilization development, including the impact of the development of technology and technology on its progress.
- The student can make the right selection of information sources, evaluate, critically analyze and synthesize this information, select and apply appropriate methods and tools, including advanced information and communication techniques, can use knowledge in the field of formulating and solving complex and unusual engineering problems, including performing tasks in new conditions.
- The student can use analytical, simulation and experimental methods, perceive systemic and non-technical aspects of the problem, including ethical ones, and make a preliminary economic assessment of proposed solutions and engineering activities, act in accordance with the given specification, design and implement devices, facilities, systems or implement processes in within biomedical engineering using appropriately selected methods, techniques, tools and materials.
|
Programme content |
Gain knowledge and develop skills in solving problems of image processing and analysis and generation of computer graphics, especially in biomedical applications. Classes include methods for improving the quality, processing, analysis and presentation of images, and presentation of models of three-dimensional spatial objects. Skills include independent development of computer programs for image processing and graphics generation. |
Assessment methods |
Positive passing each of the forms of classes is necessary. Required is active participation in the lecture discussion, passing a written test (minimum 60% of correct answers), initial self-preparation for laboratory classes (verified by the teacher), solving laboratory and project tasks (correctness is assessed by the teacher).
|
Grading policies |
A prerequisite for passing a course is positive completion of all its forms. The applicable forms of credit are left to the choice of the instructor. Assessment may include, but is not limited to, the following forms of credit: written test (min. 60% of correct answers), active participation in discussion, performance of laboratory and project exercises, preparation of a written report, computer program code with explanations, correctness of obtained results, verification of knowledge and skills during an interview. |
Course content |
Definitions of raster and vector images in two and three dimensions. Methods of image data presentation including the ability to use existing programming tools optionally C++ or Python and OpenCV, ITK, OpenGL and VTK libraries. Methods for acquisition of digital images, especially biomedical images of various modalities. Digital image enhancement methods (brightness histogram correction, linear and non-linear filters), image registration, purpose and methods of image segmentation (contour and area methods), image feature extraction and applications of data classification methods. Lossy (JPEG) and lossless compression of images and the associated risks. Computer graphics, example of vector image formats and their applications. Rendering of three-dimensional graphics, affine transformation, homogeneous coordinates, projection methods, methods of removing invisible surfaces lighting modeling, shading with Gaurod and Phong methods. Presentation of biomedical data in two- and three-dimensional spaces. |
Basic reference materials |
- Lecture notes (http://www.eletel.p.lodz.pl/pms)
- A. Materka, Elementy przetwarzania obrazów, PWN, 1991.
- R.C. Gonzales, R.E. Woods, Digital image processing, Addison-Wesley, 1992
- J.Foley, A. Van Dam, S. Feiner, R. Phillips, Intorduction to Computer Graphics - Addison-Wesley Pub. Comp. 1995
|
Other reference materials |
- Dave Shreiner, OpenGL Programming Guide: The Official Guide to Learning OpenGL, Addison-Weslay
- Gary Bradski, Adrian Kaehler, Learning OpenCV: Computer Vision with the OpenCV Library, O`Reilly
|
Average student workload outside classroom |
6 |
Comments |
|
Updated on |
2023-11-14 13:00:16 |
Archival course yes/no |
no |