Infopaket

Image processing

ДВС.1.07

Вибіркова дисципліна для ОП

First

2022/2023

8 Semester

4

PLO-1. Know, analyze, purposefully search for, and choose information and reference resources and knowledge necessary for solving professional tasks, taking into account modern achievements of science and technology. PLO-5. Know and apply relevant mathematical concepts, methods of domain, system, and object-oriented analyses, and mathematical modeling for software development. PLO-28.1. Know and have the skills to implement basic programming algorithms and data structures.

Full-time form

To successfully study the "Image Processing" discipline, the student's academic level must meet the following requirements: 1. Know: 1. Fundamentals of mathematical analysis, linear algebra, discrete mathematics, differential equations, operations research, and numerical methods. 2. Image processing software. 2. Be able to: 1. Apply basic algorithms for filtering, restoration, and recognition when processing information. 2. Apply digital information processing algorithms. 3. Possess: 1. Skills in construction, analysis, and application of mathematical methods when solving image processing problems.

Mastering the methods and acquiring theoretical and practical knowledge in the field of information technologies related to digital image processing. Image processing is becoming an indispensable tool in image analysis in all areas of applied science. Taking the course allows for new interdisciplinary interactions, combining computer science with relevant fields of research. In the course of training, students will get acquainted with the basic algorithms of digital information processing, image restoration, image compression, and pattern recognition.

1. Butakov Ye.A., Ostrovskii V.I., Fadeev I.L. Obrabotka izobrazhenii na EVM. - M.: Radio i svyaz, 1987. 2. Prett U. Tsifrovaya obrabotka izobrazhenii. – M.: Mir, 1982, t1, t2. 3. Akhmed N., Rao K.R. Ortogonalnie preobrazovaniya pri obrabotke tsifrovikh signalov. – M.: Svyaz, 1980. 4. Obrabotka izobrazhenii i tsifrovaya filtratsiya. Pod redaktsiei T.Khuanga. – M.: Mir, 1979. 5. Patrik E. Osnovi teorii raspoznavaniya obrazov. – M.: Sovetskoe radio, 1980. 6. Duda R., Khart P. Raspoznavanie obrazov i analiz stsen. – M.: Mir, 1976. 7. Maks Zh. Metodi i tekhnika obrabotki signalov pri fizicheskikh izmereniyakh. – M.: Mir, 1983, t1, t2. 8. Vasilenko G.I., Taratorin A.M. Vosstanovlenie izobrazhenii. – M.: Radio i svyaz, 1986. 9. Otnes R., Enokson L. Prikladnoi analiz vremennikh ryadov. – M.: Mir, 1982. 10. Sergienko A.B. Tsifrovaya obrabotka signalov. –M.: Piter, 2003.

Lectures, independent work, study of recommended literature, homework.

Semester assessment: The maximum number of points that can be obtained by a student is 100 points: 1. Control work #1: 50/30 points. 2. Control work No. 2: 50/30 points. Final evaluation (credit): - Credit points are defined as the sum of grades/points for all successfully assessed learning outcomes provided for in this program. - Scores below the minimum threshold level are not added. - The minimum threshold level for the total score for all components is 60% of the maximum possible number of points.

Ukrainian