Course detail
Advanced techniques of image processing
FEKT-MPZOAcad. year: 2012/2013
The theory and practice of advanced image processing techniques. Video sequence processing is included. The main areas of interest are camera model, its calibration, DFT image filtration, convolution, object recognition, biometric features recognition (skin, face, papilar lines), epipolar geometry, stereo pair analysis, correspondence problem, spatial information extraction, dynamic programming, homography, optical flow, motion in scene tracking.
Language of instruction
Number of ECTS credits
Mode of study
Guarantor
Department
Learning outcomes of the course unit
Prerequisites
Co-requisites
Planned learning activities and teaching methods
Assesment methods and criteria linked to learning outcomes
40 points work and tests done in laboratory lessons
Course curriculum
2. Intensity transformations, histogram equalization.
3. Geometric image transformations, homogenous coordinates.
4. Discreet Fourier Transform, image filtration in frequency domain.
5. Image processing in spatial domain, convolution, filtration, edge detection.
6. Basics of image segmentation, automatic threshold estimation, Viola-Jones detector.
7. Pinhole camera model, parallel projection, perspective projection, translation, rotation, calibration.
8. Homography, panorama image stitching, projective transformation, cylindrical, spherical panorama.
9. Epipolar geometry, image stereo pair.
10.Biometrical image identification.
11.Spatial information extraction, correspondence problem, dynamic programming.
12.Optical flow, scene motion estimation.
Work placements
Aims
Specification of controlled education, way of implementation and compensation for absences
Recommended optional programme components
Prerequisites and corequisites
Basic literature
HLAVÁČ V., ŠONKA M.: Počítačové vidění, Grada, Praha 1992, ISBN 80-85424-67-3. (CS)
PARKER, J. R.: Algorithms for Image Processing and Computer Vision, Wiley; Bk&CD-Rom edition 1996, ISBN: 471140562. (EN)
Recommended reading
Classification of course in study plans
Type of course unit
Lecture
Teacher / Lecturer
Syllabus
2. OpenCV library, algorithmization of processing
3. geometric image transformations, homogenous coordinates
4. DFT, image filtration, convolution
5. edge, object detection in image
5. pinhole camera model, translation, rotation, calibration
6. biometric features recognition,skin , eye iris, face, papilar lines, walking
7. camera model, parallel projection, perspective projection, translation, rotation, calibration
8. epipolar geometry, image stereo pair
9. homography, panoramatic image assembling
10. spatial information extraction, correspondence problem, dynamic programming
11. optical flow, motion in scene tracking
Laboratory exercise
Teacher / Lecturer
Syllabus
2. practical acquainting with OpenCV library, inputs, outputs, processing
3. histogram, equalization, trasholding
4. geometrical transformation
5. camera calibration
6. DFT-2D
7. test
8. edge, object detection
9. epipolar geometry
10. homography, panoramatic image assembling
11. correspondence problem, dynamic programming
12. motion in scene tracking