FPF:UF0D190 Image Analysis and Recognition - Course Information

UF0D190 Image Analysis and Recognition

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

• Multimedia Technologies (programme FPF, B1702 AplF)

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).

Activity	Difficulty [h]
Domácí příprava na výuku	24
Přednáška	24
Příprava na zkoušku	15
Zkouška	1
Summary	64

• Enrolment Statistics (Summer 2016, recent)
  
• Permalink: https://is.slu.cz/course/fpf/summer2016/UF0D190