Apply for masters program

Foundations of Computer Vision

Code – 230100   Information and computer science; section: Software of computer equipment and automation systems

Qualification (degree) – Master

Description of course modules (sections, subjects):

  1. Concept of computer vision and its use in industrial conditions.
  2. Key concepts of image identification.
  3. Methods and algorithms of image processing.
  4. Virtual reality systems and application tasks with computer vision systems.

Syllabus of the course:

Sources of digital image processing. Components of an image processing system. Elements of visual perception. Image sensing and registration. Image digitization and quantization.  Components of the computer vision system.

Image segmentation: identification of intensity discontinuity, thresholding, segmentation by separate areas. Presentation and description: presentation, boundary descriptors, area descriptors. Key components of a description, relational descriptors. Object identification: images and classes, object identification using methods of a decision theory, training algorithms, multi-layer neuron nets, structural methods of identification.

3D methods for image enhancement: gradation transformation, histogram modifications, foundations of space filtering. Frequency domain methods for image enhancement: Fourier transformation and frequency domain, smoothing using frequency domain filters, sharpening frequency domain filters, homomorphic filtering. Image reconstruction: noise models, noise reduction, filtration and types of filters. Color image processing: color models, pseudocolor image processing, color transformations, color segmentation. Morphological image processing.

Concept of virtual reality systems: construction principles, movement detectors and manipulators, application of virtual reality systems. Examples and schemes of solving problems using computer vision systems in various areas of the national economy.

Teaching methods:

  • lectures,
  • classroom group training directed by a teacher,
  • students’ independent work performed according to the teacher’s task in classrooms and on an extracurricular basis, including use of technical training aids (compulsory),
  • tutorials.

Total hours – 108.

Total credits – 3.

Laboratory work – not applicable.

Form of interim assessment – pass/fail exam.

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