Linear Systems Video System Engineering

- Know the mathematical and statistical foundations of Digital Image Processing, emphasizing linear processing. - Know the main sources of image degradation, and the possibilities of image restoration techniques. - Know the basic components of image analysis and image understanding systems. - Know elementary strategies for image segmentation, feature extraction, morphological processing and object recognition. - Know the basic tools for processing image sequences. - Use a specific software environment to implement image processing algorithms. - Implement and use basic processing tools: linear and non-linear local processing, image transform, morphological operators, basic methods for feature extraction and segmentation. - Solve complex image processing problems through the combination of basic processing blocks. - Design strategies and image processing algorithms for solving specific problems.

0. Introduction. Applications of Digital Image Processing 1. Digital image and Video 2. Pointwise transformations 3. Filtering 4. Edge detection 5. Geometric transformations 6. Image Processing in the Frequency Domain 7. Image restoration 8. Segmentation 9. Morphological image processing 10. Image Descriptors 11. Introduction to Neural Networks (NNs) 12. Convolutional Neural Networks (CNNs) for image classificacion 13. CNNs for object detection and segmentation

The course will be organized around two types of class sessions: theoretical and laboratory. THEORY The theoretical classes will consist of conventional oral sessions by the teacher, with the aim to present and discuss the fundamental concepts and tools for digital image processing, providing the students with the opportunity to ask and resolve whatever questions arise during learning. Slides, blackboard and software demonstrations will be used to support the session. LAB SESSIONS Between 25% and 40% of the course will be developed in the laboratory, with the following objectives (1) to get some skills in the use of an Image Processing Software, (2) use the image processing tools to visualize the eficacy of the methods discussed during the theoretical sessions, (3) solve simple image processing problems, and (4) complete a final lab project oriented to solve a complex problem.