UF0D190 Image Analysis and Recognition

Faculty of Philosophy and Science in Opava
Summer 2016
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 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
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/
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).
ActivityDifficulty [h]
Domácí příprava na výuku24
Přednáška24
Příprava na zkoušku15
Zkouška1
Summary64
The course is also listed under the following terms Winter 2009, Winter 2010, Winter 2011, Winter 2012, Winter 2013, Summer 2015, Summer 2017, Summer 2018.
  • Enrolment Statistics (Summer 2016, recent)
  • Permalink: https://is.slu.cz/course/fpf/summer2016/UF0D190