FPF:UF0D190 Image Analysis and Recognition - Course Information
UF0D190 Image Analysis and Recognition
Faculty of Philosophy and Science in OpavaSummer 2018
- Extent and Intensity
- 2/0/0. 5 credit(s). Type of Completion: zk (examination).
- Teacher(s)
- doc. RNDr. Stanislav Hledík, Ph.D. (lecturer)
- Guaranteed by
- doc. RNDr. Stanislav Hledík, Ph.D.
Centrum interdisciplinárních studií – Faculty of Philosophy and Science in Opava - Prerequisites (in Czech)
- UF0D206 Signal Analysis
Student musí zvládat základy lineární algebry (předměty MU/01006 nebo UF/PA128) nebo v rozsahu Části E knihy Žára, J., Beneš, B., Sochor, J. & Felkel, P. (2004), Moderní počítačová grafika, 2. vydání, Computer Press, Brno, ISBN 80-251-0454-0, dále metody zpracování jednorozměrného signálu v rozsahu kurzu Analýza signálu (UF/0D106 nebo UF/0D206).
- Course Enrolment Limitations
- The course is offered to students of any study field.
- Course objectives
- The course focuses on digital processing of two-dimensional signals (images) and multidimensional signals in physics, monitoring technology and in other areas.
- Syllabus
- 1. Mathematical description of continuous and discrete image, physiological and psychological aspects of vision, mathematical model of monochrome and color vision, image types and equipment for their capture.
2. Image pre-processing: sampling and image reconstruction, linear operators, addition and convolution, unit transformations. Geometric transformations, digital noise filtering, image sharpening and clarifying the edges, histogram and its equalization.
3. Mathematical morphology: dilation, erosion, closing and opening.
4. Image segmentation: thresholding segmentation, adaptive thresholding. Monitoring the border, Hough transform. Segmentation by area accretion and cleavage, by direct comparison with the model.
5. Feature detection and pattern recognition: global and local symptoms, evaluation of symptoms, independence to image transformations, feature statistical methods for pattern recognition, classifiers.
6. Application of selected methods in practice.
Current information and additional study materials can be found here: http://www.hledik.org/
- 1. Mathematical description of continuous and discrete image, physiological and psychological aspects of vision, mathematical model of monochrome and color vision, image types and equipment for their capture.
- Literature
- recommended literature
- SOJKA E. Digitální zpracování a analýza obrazů. VŠB-TU Ostrava, 2000. ISBN 80-7078-746-5. info
- SCHLESINGER, M.I. - HLAVÁČ, V. Deset přednášek z teorie statistického a strukturního rozpoznávání. Praha: ČVUT, 1999. ISBN 80-01-1998-5. info
- ŠONKA, M. - HLAVÁČ, V. - BOYLE, R. Image Processing, Analysis and Machine Vision. Boston: PWS, 1998. ISBN 0-534-953-93. info
- HARALICK, R. M. - SHAPIRO, L. G. Computer and Robot Vision. New York: Addison-Wesley, 1992. ISBN 0-201-56943-4. info
- Teaching methods
- One-to-One tutorial
Skills demonstration - Assessment methods
- The analysis of student 's performance
- Language of instruction
- Czech
- Further comments (probably available only in Czech)
- The course can also be completed outside the examination period.
- Teacher's information
- Semester exam has oral part only. Knowledge of the nature of discussed methods, supplemented by practical examples, are required. Knowledge of mathematical nature and pictogrammatic approach has precedence over reciting the mathematical formulas (e.g., when discussing the properties of Fourier transform, knowledge of basic transformation pairs and explaination of their properties are required).
Activity Difficulty [h] Domácí příprava na výuku 24 Přednáška 24 Příprava na zkoušku 15 Zkouška 1 Summary 64
- Enrolment Statistics (recent)
- Permalink: https://is.slu.cz/course/fpf/summer2018/UF0D190