Subject: Image processing 2 (17.D0M30 )
Native organizations units: Department of Fundamentals Sciences
Study programmes of the course:
| Type of studies | Title |
|---|---|
| Doctoral Academic Studies | Mathematics in Engineering (Godina: 2, Winter) |
Educational goal:
The educational objective of the course is to give a deeper knowledge about image processing tasks and methodologies, first introduced in Image Processing I course. The suggested topics cover main steps in image processing: image pre-processing, image segmentation, shape analysis and feature extraction, and interpretation. Additional topics are related to 3D images, colour images, and fuzzy segmented images. Such a concept provides an overview and practical understanding of this up-to-date field of applied mathematics and computer science.
Educational outcome:
Knowledge of steps and methodologies of image processing. Practical knowledge that can be applied in a variety of real world image analysis tasks.
Course content:
1. Image pre-processing (advanced): Geometric transformations. Local pre-processing (image smoothing, edge detectors, scale in image processing). Image restoration. 2. Image segmentation (advanced): Advanced edge- and region-based segmentation methods. (Hough transform, watersheds, matching, live-wire, active contours (snakes)). 3. Object recognition: Statistical pattern recognition. Optimization techniques in recognition. Recognition as graph-matching. 4. Image registration: Registration transformations (translation, rotation, scaling, projective transformations). Geometric features. Similarity measures. 5. Basics of 3D image processing. 3D vision. 3D image geometry and topology. 3D image analysis methods. 6. Basics of colour image analysis: Colour models. Colour image segmentation. 7. Fuzzy Image Analysis: Introduction to fuzzy set theory. Discrete fuzzy spatial sets. Fuzzy segmentation methods. Fuzzy shape analysis. Defuzzification Part of the course is organized in the form of independent study and research work in the field of discrete mathematics and image processing. The study and research work involves active study of primary scientific sources, organization and conduction of experiments and statistical data analysis, numerical simulations, and possibly writing a paper in the filed of discrete mathematics.
Teaching methods:
Lectures. Consultations. The lectures are organized in combined form. The presentation of the theoretical part during the lecture classes is followed by the characteristic examples which contribute to better understanding of the subject matter. In addition to lectures there are regular consultations. Through research and study work the student will, on the bases of scientific journals and other relevant literature that has been studied independently, develop further understanding of the material covered in lectures. Working with the course teacher the student develops the ability to independently work on a scientific paper.
Literature:
| Authors | Title | Year | Publisher | Language |
|---|---|---|---|---|
| razni | Odabrani stručni materijal (naučni radovi, izvodi iz predavanja i sl.) | 2000 | English | |
| 2008 | English |
Knowledge evaluation:
| Course activity | Pre-examination | Obligations | Number of points |
|---|---|---|---|
| Term paper | Yes | Yes | 20.00 |
| Lecture attendance | Yes | Yes | 10.00 |
| Oral part of the exam | No | Yes | 70.00 |
Lecturers:
doc. dr Delić Marija
Assistant Professor
Lectures
prof. dr Lukić Tibor
Full Professor
Study research work
prof. dr Lukić Tibor
Full Professor
Lectures
doc. dr Delić Marija
Assistant Professor
Study research work
Faculty of Technical Sciences
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Contact:
Address: Trg Dositeja Obradovića 6, 21102 Novi Sad
© 2024. Faculty of Technical Sciences.