-
Presentation
Presentation
This curricular unit aims to dedicate to image processing as a source of greater sensory sysem. Here are presented the various technologies of image sensors, image capture and are studied the various methods of image processing and information extraction. In the practical component it will be developed an image processing application, which will use some of the methods learned during the semester to solve a practical problem that will be proposed, using OpenCV library with c# programming language. There will also be given some notions of introduction to Artificial Intelligence applied to the images.
-
Class from course
Class from course
-
Degree | Semesters | ECTS
Degree | Semesters | ECTS
Bachelor | Semestral | 5
-
Year | Nature | Language
Year | Nature | Language
3 | Mandatory | Português
-
Code
Code
ULHT6634-24449
-
Prerequisites and corequisites
Prerequisites and corequisites
Not applicable
-
Professional Internship
Professional Internship
Não
-
Syllabus
Syllabus
1. Image processing from pixels to features; 2. Operations over images; 3. Segmentation; 4. Object detection; 5. Feature extraction; 6. Measures; 7. Analysis of applications. Online learning: Tutorials and online support.
-
Objectives
Objectives
At the end of the semester, students are expected to have: Ability to analyze 2D images and apply the necessary filters (such as rotation, translation, etc.) for a given goal; More in-depth knowledge of the C# language; Basics of artificial intelligence concepts in digital images.
-
Teaching methodologies
Teaching methodologies
The set of topics being taught puts the emphasis in the key aspects that were identified in the course objectives. On the other hand, the strong practical component of this course encourages the development of algorithms and the use of the programming language, while it stimulates problem solving using a computer.
-
References
References
1- Digital Image Processing. Rafael Gonzalez, Paul Wintz. Addison-Wesley 2- Image Analysis: principles and practice, pp. 36 a 36 e 106 a 117. Joyce-Loebl 3- Digital Image Processing and Computer Vision, pp. 130 a 173. Robert Schalkoff 4- Computer Graphics - Principles and Practice, pp. 550 a 555. Foley, van DAM, Feiner, Hughes. Addison-Wesley
-
Assessment
Assessment
A disciplina é teórico-prática, havendo uma alternância entre a componente expositiva e participativa. As aulas teóricas seguem o programa definido, apresentando os conceitos teóricos sustentados por exemplos práticos. A aprendizagem dos conceitos é validada através de pequenos exercícios em papel feitos durante a aula, que permitem ao professor aferir da eficácia das suas explicações. Nas aulas práticas os alunos aplicam os conceitos teóricos na resolução de exercícios de programação feitos em computador, de forma individual ou em grupo (máximo 3 elementos por grupo). As aulas práticas decorrem sempre em sintonia com as aulas teóricas da semana anterior.
Avaliação Contínua:
42.5% - 1 teste e um exame com nota mínima de 8 valores.
7.5% - 10 quizzes onde contam os 9 melhores (quizzes semanais).O teste e os quizzes juntos terão de ter uma nota mínima de 9.5 (componente teórica).
50% - Projeto em grupos de 2/3 com defesa presencial em grupo. A nota do projeto tem nota mínima de 9.5 (componente prática).
Época de recurso/especial:
50% - Exame 50% - Project. É necessário ter 9.5 de nota mínima em cada componente para aprovar à disciplina.
-
Mobility
Mobility
No
