Hungarian Association for Image Processing and Pattern Recognition


Academic courses in Hungary supervised by the members of KéPAF:

Corvinus University of Budapest

Computer Vision and Image Processing

Machine vision systems - hardware and software aspects, Algorithms of Image Processing for Colour and Shape characterisation, Applications for Horticulture and Food research.

Óbuda University

Fundamentals of Computer Vision and 3D Modeling

Fundamentals of computer vision, sampling, quantization, representation. Basic image processing. Preprocessing, noise removal, morphology, histogram calculation and transformations. Sharpening. Normalization in spatial and intensity domain. Global, local and additive binarization. Edge detection, Canny algorithm, SUSAN method. Curve fitting on contour points. Split and merge for contours. Corner points, Harris detector. Basics of robot modeling. Homogeneous coordinates and transformations. Denavit-Hartenberg model, using external coordinates for robot modeling: Euler angles. Direct and inverse geometrical problem. Using visual information in robotics. Connection between the camera and work space frame, 3D-2D projections.

Computer Vision

Image pyramids. Camera models and calibration. Segmentation. Split and merge for regions. Skeletonization. Texture features. Image processing in frequency domain. Contour detection in given directions. Hough transformation. Edge tracking. Shape descriptors, invariant features, Fourier descriptors. Object recognition. Image compression. Handling video streams. Applications: biometrical systems, face detection and recognition. Color models, transformations and color normalization. Stereo, epipolar geometry, disparity maps. Motion detection, optical flow, motion tracking. Active contours, Using snakes for segmentation and tracking. Application of omnidirectional vision sensors. Robot vision. Obstacle avoiding, mapping, navigation. Appearance and marker based methods.

Budapest University of Technology and Economics


3D scanning technologies (CT, MRI, PET). Sampling theory, Fourier analysis. Approximation theory: design of reconstruction filters, approximation, interpolation, quasi-interpolation. Radon transform, tomographic reconstruction methods: algebraic reconstruction, filtered back-projection, statistical methods. 3D image processing: filtering, segmentation, compression. Indirect visualization: Fourier volume rendering, marching cubes, Monte Carlo volume rendering. Direct visualization: ray casting, splatting, shear-warp transformation. GPU-accelerated volume rendering. Virtual endoscopy: segmentation, navigation. Non-photorealistic volume rendering.

3D Reconstruction from Video

University of Debrecen

Mathematical Background of Image Processing

Image Processing Methods

Shape Recognition

Medical Image Processing

Eötvös Loránd University

Digtal Image Analysis I-II.

Dennis Gabor College, Budapest

Digital Image Processing

John von Neumann University, GAMF - Faculty of Engineering and Computer Science, Kecskemét

Signal and Image Processing

Metrology of Industrial processes

Intelligent Systems II., Object Recognition

Industrial Image Processing

University of Pannonia

Image Processing

Measuring Image Information


Pázmány Péter Catholic University, Faculty of Information Technology and Bionics

Basic Image Processing

A basic course of the international Image Processing and Computer Vision (IPCV) Erasmus Mundus master program. Main topics: History and Applications, Digital representation of an image, Color Spaces, 2D convolution and its applications, Canny edge detector, Hough transformation, Image Enhancement, Fourier analysis, Texture analysis, Image recovery, Image segmentation: Intro, K-means and Morphology, Watershed and Mean shift, Descriptors: Harris, SIFT, HOG, LBP, binary descriptors, introduction to machine learning and deep learning.

University of Szeged

Digital Image Processing

Imaging (sampling and quantizing). Fourier transform. Convolution. Point operations. Histogram transformations. Blurring/filtering image space. Blurring/filtering in frequency space. Image restoration. Edge detection. Segmentation. Shape representation. Image coding, compressing.

Advanced Image Processing

Color images and image processing. Advanced image segmentation methods. Skeletonization and its applications. Mathematical morphology. Binary image processing. Texture analysis. Morphing, Warping. Image registration. Motion and tracking. Fuzzy segmentation.

Introduction to Image Processing

Image processing systems. Image representation on computers. Sampling. Quantizing. Image enhancement. Point operations. Histogram, histogram transformations, equalization. Image blurring. Fourier transform. Convolution. Convolution theorem. Image filtering, filters. Edge enhancement, edge detection, gradient operators. Line detection, Hough transform. Image segmentation. Point, line, edge detection. Region description. Image representation. Border matching, region growing, region clustering, texture. Morphology: dilate, erode, opening and closing. Morphology operators. Hit or miss transform. Morphology algorithms. Image compression, coding redundancy, psycho-visual redundancy. Measuring distortion of information. Information content of images, Shanon’s coding theorem. Huffman code. Run-length encoding. Arithmetic encoding. Bit layers. Transformation coding. Image compression standards. Fuzzy connectivity. Fuzzy segmentation. Statistical pattern recognition. Cluster analysis, MacQueen k-means, ISODATA, neural nets.

Image reconstruction

Images, projections, reconstruction, reconstruction problem. Projection-slice theorem. reconstruction with convolution. Algebraic reconstruction techniques. Other reconstruction techniques. Reconstruction of 3D objects. Computed Tomography. Reconstruction of medical images. Applications of tomography. Discrete tomography and its applications.

Image Registration

Image registration: basics. Imaging techniques, image features. Displaying of results. Geometrical transformations. Interpolation techniques. Point based matching and error analysis. Matching point clouds. Contour/surface matching. Reducing image information. Point similarity measures. Automatic registration techniques. Object tracking. Surgery planning applications. Nonlinear registration. Point distribution model and its applications. ITK, VTK, Slicer, ImageJ, Drop.

Medical Image Processing

Electromagnetic radiation, radioactive decay, positron annihilation. X-Ray tube. Photo scattering. signal-to-Noise ratio. scatter reduction. Angiography. CT, sinogram, reconstruction. Nuclear medicine, PTM. Gamma camera, calibration. Quality control. ROI, time-activity curve, parametric images, functional images, factor analysis. Hearth blood flow. Clearance. ECG gated hearth study. SPECT, corrections. PET, positron camera, attenuation, time of flight. Two compartment model. Patlak method. Ultrasound, attenuation correction, A-scan, M mode, B mode. Doppler. Magnetic resonance, Larmor frequency, relaxation. 90-FID, spin-echo, inversion-sequence. Gradient magnetic field. Image registration. image fusion. 3D rendering (surface, volume).

Computer Vision

Human and computer vision. Models of vision (Marr, Gestalt rules). Geometry of a camera, parameters of 3D->2D projection. Single image surface reconstruction using: Shading based methods, texture based methods. Measuring motion, optical flow. Motion as transformation: parametric motion models. Motion-tracking. Video mosaicing. Strereo vision, epipolar geometry. Essential Matrix, Fundamental Matrix. 3D reconstruction from image pair. 3D reconstruction from multiple image pairs. Motion based reconstruction. 3D reconstruction and generation of virtual views.

Segmentation of Digital Images

The role of segmentation in computer vision. Features in segmentation: color (linear and non-linear). Texture: static features, MRSAR, Gabor filters. Motion: measuring displacement, segmentation problems according motion. Segmentation algorithms: edge detection: Sobel, Canny, Diriche. Detecting homogeneous regions: split-merge, k-means, mean shift, watershed.

Digital Topology and Mathematical Morphology

Digital images, neighborhoods, Jordan-property. Topological features, holes. Image operation, addition, reduction, topology-preserving, topological kernel. Simple points in 2D. Simple points in 3D. Topology preserving parallel reduction. Erosion, dilate, opening, closing, morphological filtering. Border subtraction, region filling. skeletonization. Hit-or-Miss transform, thinning, pruning, convex hull. Morphological operations on multi-level images.

Discrete Tomography

Basic problems of Discrete Tomography. Binary tomography and its applications. Reconstruction of binary matrices from 2 projections. hv-convex polinomios. Connection of the reconstruction problem with the 2SAT expressions. Reconstruction from more than two projections. Reconstruction as optimization problem. Pixel based and object based reconstruction. reconstruction of multi component object using DT. Preprocessing methods. Using DT for non-destroying studies. Emission discrete tomography an its applications.

Energy Minimization Methods in Image Processing

Markov fields and their applications in image segmentation. Active contour. Variational methods. Shape description. Using higher order information in image segmentation.

Fuzzy techniques in Image Processing

Basics, fizzy sets and operations, fuzzy logic. Fuzzy image processing systems. Fuzzy geometry. Fuzzy image enhancement. Fuzzy edge detection. Fuzzy image segmentation. Fuzzy mathematical morphology. Fuzzy connectivity and variations. Medical image segmentation using fuzzy connectivity.

Image Registration and its Medical Applications

Application areas of registration. Major component of the registration algorithm. 3D medical imaging. Geometric transformations, interpolation techniques. Point based registration. Surface matching algorithms. Automated algorithms. Similarity measures. Image fusion. Computer aided Surgical planning. Nonlinear registration.

Skeletonization in Image Processing

Definitions of a skeleton. Distance-transform and algorithm. Skeletonization with distance-transformation. Voronoi and Delaunay decomposition. Thinning. Thinning algorithms in 2D and 3D.