- Course
- 2021-2022
- Semester
- 1
- ECTS
- 6
- Type
- Compulsory
- University
- UDC and UVigo
Subject objectives
The aim of this course is to become familiar with the fundamental characteristics of the
digital image and its forms of representation, the description of visual content through
local characteristics of colour, shape and texture, and the practical application of these
concepts to problems of image processing and analysis.
Contents
Image representation and modeling: space-frequency, orientation and phase, space-scale
Wavelets and filter banks
Image coding and reconstruction
Description of colour, shape and texture
Image modelling and description applications
Basic and complementary bibliography
Basic
1. Bovik, Alan. «The essential guide to image processing». 1st Edition, 2009.
ISBN: 978-0-12-374457-9.
2. Bovik, Alan (Ed.). «Handbook of image and video processing». 2nd Edition,
2005. ISBN: 978-0-12-119792-6.
3. Mallat, Stephane. «A wavelet tour of signal processing: The sparse way». 3rd
Edition, 2009. ISBN: 978-0-12-374370-1.
4. Nixon, Mark. «Feature extraction and image processing for computer vision».
3rd Edition, 2012. ISBN: 9780123965493.
5. Sonka, M; Hlavac, V.; Boyle, R. «Image Processing, Analysis, and Machine
Vision». 3rd Edition, 2009. ISBN: 978-0-49-508252-1.
6. Forsyth, David A; Ponce, Jean. “Computer Vision: A Modern Approach”.
Pearson. 2nd Edition, 2012. ISBN: 978-0-13608-592-8.
7. Szeliski, Richard. “Computer Vision: Algorithms and Applications”. Springer.
1st Edition, 2010. ISBN 978-1-84882-934-3.
8. Petrou, Maria; García-Sevilla, Pedro. «Image processing: Dealing with texture».
2006. ISBN: 978-0-470-02628-1.
9. Mirmehdi, M.; Xie, X.; Suri, J. (Eds.). «Handbook of texture analysis». 2008.
ISBN: 978-1-84816-115-3.
10. Recent papers from relevant scientific journals and conferences: IJCV, IEEE TPAMI, ICCV, CVPR, NIPS, ECCV, etc.
Competencies
Study programme competences: Specific
A1 CE1 – To know and apply the concepts, methodologies and technologies of image processing
Study programme competences: Basic / General
B1 CB6 – To possess and understand knowledge that provides a basis or opportunity to be original in the development and/or application of ideas, often in a research context
B2 CB7 – That students are able to apply their acquired knowledge and problem-solving skills in new or unfamiliar environments within broader (or multidisciplinary) contexts related to their area of studyB6 CG1 – Ability to analyze and synthesize knowledge
B8 CG3 – Ability to develop computer vision systems depending on existing needs and apply the most appropriate technological tools
Study programme competences: Transversal / Nuclear
C1 CT1 – Practice the profession with a clear awareness of its human, economic, legal and ethical dimensions and with a clear commitment to quality and continuous improvement
C2 CT2 – Ability to work as a team, organize and plan
Teaching methodology
Guest lecture / keynote:
speech Participatory lessons with the aim of learning the theoretical content of the subject
Case study:
Elaboration and presentation of selected state-of-the-art methodologies related to the subject.
Objective test:
Continuous self-evaluation tests during the course. Evaluation by examination at the end of the course as an alternative.
Laboratory practice:
Analysis and resolution of practical cases with the aim of strengthening the practical application of the theoretical content. Practice in computer classrooms, learning based on the resolution of practical cases, autonomous work and independent study of the students, and group
work and cooperative learning.
Research (Research project):
Learning based on the resolution of practical cases, autonomous work and independent study of the students, and group work and cooperative learning.
See Contingency Plan for alternative scenarios.
Evaluation system
-Case study (15).
Competences: A1 B1 B2 B6
B8 C1 C2
Elaboration and presentation of works on selected state-of-the-art
-Objective test (25):
Competences: A1 B1 B2 B6
B8 C2 C1
Continuous self-evaluation tests during the course. Evaluation by examination at the end of the course as an alternative
-Laboratory practice (40)
Competneces: A1 B1 B2 B6
B8 C1 C2
Analysis and resolution of practical cases with the aim of strengthening the practical application of theoretical content
– Research (Research project) (20):
Competences:A1 B1 B2 B6
B8 C1 C2
Resolution of practical cases of application of the subject through autonomous work of the student, and using the techniques learned during the course
See Contingency Plan for alternative scenarios.
Studying time and personal work
Recommended study time for students is about 2 hours per week. Additionally, we estimate that they should spend about 6,5 hours / week working in a number of assignments. All of these activities add up to around 120h/semester.
Subject study recommendations
Subjects that are recommended to be taken simultaneously:
Fundamentals of Machine Learning for Computer Vision /614535007
Fundamentals of Image Analysis and Processing/614535001
Observations
Contingency plan:
1. Modifications to the contents No change
2. Methodologies All activities are maintained.
The teaching will be online and the lessons will take place synchronously in the official schedule of classes. It may be that, for reasons of inconvenience, some of the classes will be held asynchronously, which will be communicated to the students in advance.
3. Mechanisms for personalized attention to students The tutorials will be telematic and will require an appointment.
4. Modifications in the evaluation No change in the evaluation.
Evaluation activities that cannot be carried out in person will be carried out telematically through the institutional tools in Office 365 and Moodle. In this case, a series of validation measures will be required, which will require the students to have a device with a microphone and a camera, while appropriate validation software is not available. An interview may be arranged with each student to comment on or explain part or all of the tests carried out. In these scenarios, some of the activities under each heading may be modified, adapting them to the situation, but not their overall contribution to the final grade (the weighting percentage).
5. Modifications to the bibliography or webgraphy No change