FPF:UFPF010 Analysis and digital image pro - Course Information
UFPF010 Analysis and digital image processing
Faculty of Philosophy and Science in OpavaSummer 2021
- Extent and Intensity
- 2/2/0. 6 credit(s). Type of Completion: zk (examination).
- Teacher(s)
- doc. RNDr. Stanislav Hledík, Ph.D. (lecturer)
Mgr. Adam Hofer (seminar tutor)
RNDr. Jan Novotný, Ph.D. (lecturer) - Guaranteed by
- doc. RNDr. Stanislav Hledík, Ph.D.
Centrum interdisciplinárních studií – Faculty of Philosophy and Science in Opava - Timetable
- Mon 15:35–17:10 LPS
- Timetable of Seminar Groups:
- Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- Computational Physics (programme FPF, N1701 Fyz)
- Course objectives
- Course is aimed at digital processing, analysis and recognition of image data and their applications in natural sciences, especially in physics and in measuring and monitoring technology. The lectures are supplemented by practical demonstrations and interactive demonstrations.
- Syllabus
- Introduction. Mathematical description of the image : continuous and discrete, physiological and psychological aspects of vision, mathematical model monochrome and color vision, image types and equipment for their capture.
Mathematics for image processing. Space of the image signal, its properties and operations over it. The transformation of image signals (Fourier, cosine, wavelet, general unitary ). Stochastic description of image signals.
Image preprocessing. Sampling, quantization and image reconstruction, aliasing.
Image processing point, algebraic and geometric transformations. Spot Image operations. Brightness histogram, histogram equalization. Gamma correction, contrast enhancement and related transformations. Algebraic transformations of images. Geometric transformations.
Image processing with circuit operations. Linear and nonlinear filtering. Recursive filtering, recursive filtering. Degradation and image reconstruction. Wiener filtering. Morphological processing ( dilation, erosion, opening and closing ). Image sharpening and clarifying the edges.
Image segmentation. Edge detection and territories joining edges and regions detection corners. The processing of digital images.
Feature detection and pattern recognition. Global and local symptoms, evaluation of symptoms, independence to image transformations, feature statistical methods for pattern recognition, classifiers.
Application of selected methods in practice - a case study using the software Mathematica.
- Introduction. Mathematical description of the image : continuous and discrete, physiological and psychological aspects of vision, mathematical model monochrome and color vision, image types and equipment for their capture.
- Literature
- Language of instruction
- Czech
- Further comments (probably available only in Czech)
- Study Materials
The course can also be completed outside the examination period. - Teacher's information
- The attendance at lectures is recommended. It can be substituted by the self-study of recommended literature and individual consultations. Tutorial attendance compulsory (min. 80%).
- Enrolment Statistics (Summer 2021, recent)
- Permalink: https://is.slu.cz/course/fpf/summer2021/UFPF010