Image Processing and Analysis in Engineering

Code:

MMC018

Acronym:

PAIE

Keywords
Classification	Keyword
OFICIAL	Engineering

Instance: 2022/2023 - 1S

Active?	Yes
Web Page:	http://www.fe.up.pt/~tavares
Responsible unit:	Industrial Drawing Section
Course/CS Responsible:	Master in Computational Mechanics

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
MMC	0	Syllabus since 2011/12	2	-	7,5	70	202,5

Teaching language

Suitable for English-speaking students

Objectives

General Objectives:

The domain of Image Processing and Analysis has raised potential in several areas of the human knowledge as, for example, in industry, biomechanics, bioengineering, man/machine interfaces, medicine, surveillance, biometry and virtual reality.

The course of Image Processing and Analysis in Engineering has an integrated perspective as it combines knowledge of different scientific areas; namely, of psychology, computers science, systems engineering, computational mechanics and systems modelling.

 

Specific Objectives:

To provide to the students knowledge in the multidisciplinary area of Image Processing and Analysis, as in the scope of biological vision processes as well as in the scope of methods and computational systems of image processing and analysis, in particularly in engineering.

Learning outcomes and competences

At the end of the course of Image Processing and Analysis in Engineering, the students should be able of:

1. Understand the human visual perception system;
2. Understand the process of digital images formation;
3. Know the main methods of image processing;
4. Know the main methods of image analysis;
5. Explain and develop computational systems of representation and analysis of objects in images, of segmentation, tracking and analysis of motion and deformation in image sequences as well as of 3D reconstruction of objects from images.

 

Working method

Presencial

Pre-requirements (prior knowledge) and co-requirements (common knowledge)

It is desirable that students have prior knowledge of computer programming.

Program

Programmatic Content:

The main subjects to be considered in the course of Image Processing and Analysis in Engineering are: Human Visual Perception System, Image Acquisition and Processing, 3D Vision, 3D Geometry and 3D Image. Thus, basic methods of Image Processing and Analysis will be studied, as well as advanced methods of the same domain; in particular, the Segmentation, Tracking and Analysis of Motion and/or Deformation in image sequences, the Recognition and Registration of objects in images and the Reconstruction of the 3D Shape of objects from images.

Along the course, some application examples in several domains of the knowledge of the techniques of Image Processing and Analysis studied will be verified and analyzed, as in engineering, biomechanics and medicine.

 

The programmatic content of the course is organized in six main modules:

Presentation and Introduction - 4 hours, Visual Perception - 3 hours, Acquisition, Image Processing - 10 hours, Image Analysis - 20 hours, 3D Vision, 3D Geometry and 3D Image - 8 hours, Applications Examples - 5 hours.

Mandatory literature

Freeman, Herbert 340; Machine Vision. ISBN: 0-12-266720-4
Soares, Olivério Delfim Dias 340; Optical metrology. ISBN: 90-247-3517-3
ULL; Applied image processing. ISBN: 033358242X
Gonzalez, Rafael C; Digital image processing. ISBN: 0-201-50803-6
Shapiro, Linda G. 340; Computer Vision, Graphics, and Image Processing. ISBN: 0734-189X
Schalkoff, Robert J.; Digital Image Processing and Computer Vision. ISBN: 0-471-50536-6
Yoo, Terry S. 340; Insight into images. ISBN: 1-56881-217-5

Teaching methods and learning activities

The course of Image Processing and Analysis in Engineering is based on theoretician-practical lessons.

The theoretician-practical lessons are dedicated to present the methods and computational algorithms and for the analysis of their application in several study cases; manly, in real cases involving pertinent problems in engineering.

Whenever possible, researchers, whose scientific works are relevant in the domain of Image Processing and Analysis, will be invited to present their works; those presentations will be open to the related scientific community.

 

When the number of students enrolled is small, the course works in a tutorial basis.

Software

OpenCV
CMIS – Contour Matching Image Software
VXL – C++ Libraries for Computer Vision Research and Implementation
ITK – Insight Segmentation and Registration Toolkit
CVIPtools
The Mathworks - Matlab - Release 11.1
VTK – The Visualization ToolKit, Kitware Inc.

keywords

Technological sciences > Technology > Computer technology > Image processing
Physical sciences > Mathematics > Computational mathematics
Physical sciences > Computer science > Programming
Technological sciences > Technology > Computer technology > Signal processing

Evaluation Type

Distributed evaluation without final exam

Assessment Components

Designation	Weight (%)
Defesa pública de dissertação, de relatório de projeto ou estágio, ou de tese	10,00
Trabalho escrito	25,00
Trabalho laboratorial	65,00
Total:	100,00

Amount of time allocated to each course unit

Designation	Time (hours)
Elaboração de projeto	75,00
Estudo autónomo	65,00
Frequência das aulas	25,00
Total:	165,00

Eligibility for exams

To complete this course the students must attain the required frequency of the practical classes.

The students must also undergo all components of evaluation, which includes the delivery of the practical project, and its presentation and discussion.

Calculation formula of final grade

The evaluation system of the course of Image Processing and Analysis in Engineering is composed by the accomplishment, presentation and discussion of an individual practical project, which can be complemented with the completion of a written exam.

The practical project to be developed must have an integrator view and be concerned to a concrete problem of the engineering area. The subject of each project will have to be agreed between each student and the professor. The work done will have to be described in a written report to be delivered to the professor until the end of the semester and public presented and discussed.

The final grade of the practical project and also of the course will be obtained considering the computational work developed - 65%, written report - 25%, and public presentation - 10%.

Examinations or Special Assignments

Not applicable.

Special assessment (TE, DA, ...)

On the special examination periods, the students that are dismissed from attending classes, accordingly to the terms of items a) and b) of number 3 of Article 4 of the General Evaluation Rules, will be called to do a written exam and a practical project.

Classification improvement

According to Article 10 of General Evaluation Rules of FEUP.