Personal tools
Log in

Digital Image Processing and Analysis

COURSE: Digital Image Processing and Analysis

Code: ФЕИТ05023

ECTS points: 6 ECTS

Number of classes per week: 3+0+0+3

Lecturer: Assoc. prof. Zoran Ivanovski

Subject of the course content:

The digitized image and its properties. Data structures for image analysis. Image pre-processing: Luminance transformations; Geometric transformations; Local pre-processing; Image restoration. Advanced segmentation techniques: Thresholding; Edge-based segmentation; Region-based seg mentation. Advanced optimal border and surface detection approaches. Shape representation and description: Region identification; Contour-based shape representation and description; Region-based shape representation and description; Shape classes. Object recognition: Knowledge representation; Statistical and syntactic pattern recognition; Recognition as graph matching; Optimization techniques in recognition. Mathematical morphology: Basic concepts and morphological transformations; Topological processing. Texture: Statistical texture description; Syntactic texture description methods; Hybrid texture description methods; Texture recognition method applications. Image understanding: Image understanding control strategies; Active contour models and point distribution models; Pattern recognition methods in image understanding; Scene labeling and constraint propagation; Semantic image segmentation and understanding. Motion analysis: Differential motion analysis methods; Optical flow; Analysis based on correspondence of interest points; Kalman filters. 3d vision: 3d vision tasks; Geometry for 3d vision; Radiometry and 3d vision.


  1. Milan Sonka, Vaclav Hlavac, Roger Boyle, “Image Processing, Analysis and Machine Vision”, Chapman & Hall, 3rd ed., 2008.
  2. Rafael C. Gonzalez, Richard E. Woods, “Digital Image Processing”, Prentice Hall, 3rd ed., 2007.
  3. Richard Hrtley, Andrew Zisserman, “Multiple View Geometry in Computer Vision”, Cambridge University Press, 2nd ed., 2003.