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Vision-Based Systems

Code: EEC0100     Acronym: SBVI

Keywords
Classification Keyword
OFICIAL Automation, Control & Manufacturing Syst.
OFICIAL Basic Sciences for Electrotechnology

Instance: 2015/2016 - 1S

Active? Yes
Web Page: http://www.fe.up.pt/si/conteudos_adm.conteudos_list?pct_pag_id=1639&pct_parametros=p_ano_lectivo=2009/2010-y-p_cad_codigo=EEC0100-y-p_periodo=1S
Responsible unit: Department of Electrical and Computer Engineering
Course/CS Responsible: Master in Electrical and Computers Engineering

Cycles of Study/Courses

Acronym No. of Students Study Plan Curricular Years Credits UCN Credits ECTS Contact hours Total Time
MIEEC 46 Syllabus 4 - 6 56 162
Mais informaçõesLast updated on 2015-07-31.

Fields changed: Components of Evaluation and Contact Hours, Resultados de aprendizagem e competências

Teaching language

Portuguese

Objectives

The main objectives to attain are the acquisition of knowledge on automatic vision systems, not only on the elements that constitute their modular structure, but also on the technology used in their implementation.

Learning outcomes and competences

1. Acquisition of knowledge on automatic vision systems, not only on the elements that constitute their modular structure, but also on the technology used in their implementation (CDIO Syllabus 1.3, 1.4, 2.1, 2.3).
2. Demonstration of skills on the design, projection and implementation of automatic vision systems (CDIO Syllabus 4.2, 4.3, 4.4, 4.5).
3. Development of organisational skills, as well as autonomous work and bibliography research (CDIO Syllabus 2.4, 2.5, 3.3).
4. Demonstration of skills on teamwork (CDIO Syllabus 2.5, 3.1).
5. Development and demonstration of skills on written and oral communication (CDIO Syllabus 3.2)

Working method

Presencial

Program

1. Introductio. General structure of a vision-based system
2. Conditioning of an acquisition environment
3. Acquisition and formation of digital images
4. Preprocessing. Image operators. Application on image enhancement
5. Mathematical morphology
6. Image segmentation
7. Image analysis and representation
8. Image recognition and classification

Mandatory literature

Gonzalez, Rafael C; Digital image processing. ISBN: 0-20-118075-8
Rafael C. Gonzalez, Richard E. Woods, Steven L. Eddins; Digital image processing using Matlab. ISBN: 0-13-008519-7

Complementary Bibliography

Steger C., Ulrich M. Wiedemann C; Machine Vision Algorithms and Applications, Wiley, 2008. ISBN: 978-3-527-40734-7
Milan Sonka, Vaclav Hlavac, Roger Boyle; Image processing, analysis and machine vision. ISBN: 978-0-495-24428-7
E. R. Davies; Machine Vision: Theory, Algorithms, Practabilities, Morgam Kaufmann, 205. ISBN: 0-12-206093-8

Teaching methods and learning activities

Theoretical classes: presentation of themes, practical demonstration and case analysis


Theoretical-practical classes:
Problem solving, experimentation and testing on Matlab (toolbox of Image Processing), development of solutions on Matlab

Practical assignment outside classes:
Students have to do a mini-project (2/3 students) on themes chosen by them, in the area of “object recognition”, “defect detection and quality control”, “detection and object tracking”, “video surveillance”, etc
Students will also have to write a report and to orally present their project.

Software

The Mathworks - Matlab - Release 11.1

keywords

Technological sciences > Engineering > Electrical engineering

Evaluation Type

Distributed evaluation with final exam

Assessment Components

Designation Weight (%)
Exame 70,00
Trabalho laboratorial 30,00
Total: 100,00

Amount of time allocated to each course unit

Designation Time (hours)
Estudo autónomo 50,00
Frequência das aulas 72,00
Trabalho laboratorial 40,00
Total: 162,00

Eligibility for exams

Assessment components:
- Practical assignment (2/3 students) and report (PA);
- Oral presentation of the practical assignment (OP);
- Final Exam (FE).

Students have to do the practical assignment, as well as the oral presentation and report, to be admitted to exams.
The mark of the continuous assessment component will be based on professors’ opinion regarding students’ performance during the preparation of the project, as well as the quality of the report and presentation.

Practical assignment – CDIO Syllabus assessed: 1.3, 1.4, 2.1, 2.3, 2.4, 2.5, 3.1, 3.3, 4.2, 4.3, 4.4, 4.5.
Oral Presentation – CDIO Syllabus assessed: 3.1, 3.3, 4.2, 4.3, 4.4, 4.5.
Final Exam- CDIO Syllabus assessed: 1.3, 1.4, 2.1, 2.3, 4.2, 4.3, 4.4, 4.5.

Calculation formula of final grade

Final Mark will be based on the mark of the continuous assessment component (AD) and on the final exam (NE). The same formula apply for recurso season and classification improvement.

Final markl=0.3*AD +0.7*NE

Examinations or Special Assignments

The above mentioned project

Special assessment (TE, DA, ...)

The only students with a special status are working-students. They have to do a practical assignment on the themes above mentioned. However, its length may be shorter.
Working-students can ask professors for a theme at the beginning of the semester, so that they

Classification improvement

Students cannot improve the mark of the continuous assessment component. However, students can improve the mark of the exam.

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