Опис навчальної дисципліни

This course will familiarize students with the peculiarities of development and software implementation of image recognition methods, tools and algorithms. The course covers the basic algorithms of computer vision: preprocessing, filtering, segmentation, feature extraction, recognition, and image classification. Objective: to provide students with the necessary theoretical and practical knowledge of the application of image recognition methods and systems. Formation of practical skills that would allow students to effectively apply knowledge in the tasks of assigning source data to a certain class by identifying essential features that characterize this data from the total mass of non-essential data. After completing this course, the student will: – Know: the basics of image recognition theory: basic concepts and concepts of the theory, image recognition; basic methods of Image Recognition; knowledge of the main tasks of computer vision and ways to solve them; the theory of searching for objects in images: algorithms used to localize and detect objects; features of the image recognition library – OpenCV. – Be able to: classify and solve problems related to image recognition; implement basic Image Recognition algorithms; develop their own ways to solve the simplest problems of image processing and image recognition; analyze, evaluate and select existing algorithms to solve problems; be able to use computer vision libraries such as OpenCV; conduct experimental research in the field of image recognition and image processing; work independently with educational and scientific and technical literature on image processing.