Close Help Print Course module: 191210910 191210910 Image Processing and Computer Vision Course info Course module 191210910 Credits (ECTS) 5 Course type Course Language of instruction English Contact person dr.ir. M. Abayazid, PhD E-mail m.abayazid@utwente.nl Lecturer(s) Examiner dr.ir. M. Abayazid, PhD Contactperson for the course dr.ir. M. Abayazid, PhD Examiner dr. G. Dagnino Academic year 2022 Starting block 1A Remarks Only for students who need to re-take the exam from last year. Application procedure You apply via OSIRIS Student Registration using OSIRIS Yes Aims After attending this course, the student will know and will be able to: Apply fundamental signal processing techniques on 2D images Identify and apply image restoration methods to filter image artefacts such as image noise, distortion and blurring Recognize and apply advanced image processing techniques including geometrical transforms, edge and line detection and morphological operations Describe image formation models such as geometric camera models and perspective projection Implementation of computer vision techniques such as camera calibration and rectification, and structure image analysis Describe and apply computer vision and image processing algorithms to solve a practical problem in Matlab and evaluate the performance of the proposed implementation Content This course is offered one last time in the academic year 22-23 for those who need to re-take the exam. All others: please refer to the new course 202200103 Image Processing and Computer Vision. The course familiarizes students with digital image processing and computer vision techniques. It provides the fundaments for 2-D signal processing applied to digital images. It also discusses techniques for the extraction of 2D, 3D, or 4D information that is represented by a digital image (or image sequence). Examples of computer vision tasks are: a) the detection, e.g. checking the presence of an object or event. b) The recognition or identification of an object or person. c) The measurement of the parameters of an object, e.g. position, size, shape. d) Motion analysis of objects. The topics of the course include image formation and acquisition, 2D Fourier transforms, image operations, image segmentation, regional description, recognition and parameter estimation. The course involves practical work in which the students design a vision system for a simple application. As such, the student acquires programming skills using Matlab and its image processing toolbox. Examples of design tasks that students can select are: a) Virtual advertising: inserting virtual advertising images into recorded movies of sports events   b) Motion analysis: tracking an object in a cluttered movie. c) 3D face reconstruction from 3 images d) 3D tracking of facial point features. This course is mandatory for the follow-up course: 'advanced computer vision and pattern recognition'. Content Image formation, image operations and image analysis. Assessment Individual assignments (30%) Group project + Oral discussion (50%) Written exam (20%)   Assumed previous knowledge Linear Algebra Participating study Master Electrical Engineering Participating study Master Interaction Technology Participating study Master Mechanical Engineering Participating study Master Biomedical Engineering Required materials Course material Lecture notes made available via website Course material Syllabus 3D Computer Vision (made available via website) Recommended materials Literature M. Sonka, V. Hlavac, R. Boyle: Image Processing, Analysis, and Machine Vision, 3rd edition, Thomson, 2008. This book will be used in the follow-up course 'advanced computer vision and pattern recognition'. Literature R.C. Gonzales, R.E. Woods: Digital Image Processing, 2nd edition, Prentice Hall, 2002. Literature D.A. Forsyth, J. Ponce: Computer Vision - a Modern Approach, Prentice Hall, 2003 Instructional modes Self study without assistance Tests Assignments, Group Project, Exam Close Help Print