Type A
|
Code |
Competences Specific | | A7 |
Capacitat per definir, avaluar i seleccionar plataformes hardware i software per al desenvolupament i l’execució de sistemes, serveis i aplicacions informàtiques. |
| CP3 |
Capacitat per avaluar la complexitat computacional d'un problema, conèixer estratègies algorísmiques que puguin conduir-ne a la resolució i recomanar, desenvolupar i implementar la que garanteixi el millor rendiment d'acord amb els requisits establerts.
|
| CP5 |
Capacitat per adquirir, obtenir, formalitzar i representar el coneixement humà en una forma computable per resoldre problemes mitjançant un sistema informàtic en qualsevol àmbit d'aplicació, particularment els relacionats amb aspectes de computació, percepció i actuació en ambients o entorns intel ligents.
|
| CP7 |
Capacitat per conèixer i desenvolupar tècniques d'aprenentatge computacional i dissenyar i implementar aplicacions i sistemes que les utilitzin, incloent-hi les dedicades a extracció automàtica d'informació i coneixement a partir de grans volums de dades.
|
Type B
|
Code |
Competences Transversal |
Type C
|
Code |
Competences Nuclear | | C4 |
Be able to express themselves correctly both orally and in writing in one of the two official languages of the URV |
Type A
|
Code |
Learning outcomes |
| A7 |
Dissenya aplicacions orientades a inspecció i control de qualitat
| | CP3 |
Coneix i sap utilitzar les tècniques de preprocessament, segmentació i classificació d'imatges
Dissenya aplicacions orientades a inspecció i control de qualitat
| | CP5 |
Coneix les etapes que integren un sistema de visió per computador
Coneix el procés de formació de la imatge
| | CP7 |
Sap aplicar els mètodes bàsics de la Visió per computador per a la resolució de problemes específics
Dissenya aplicacions orientades a inspecció i control de qualitat
|
Type B
|
Code |
Learning outcomes |
Type C
|
Code |
Learning outcomes |
| C4 |
Produce grammatically correct written texts
Produce well-structured, clear and rich written texts
|
Topic |
Sub-topic |
Tema 1.- Introduction |
Concept and objectives of Computer Vision. Image acquisition. Levels of image processing. |
Tema 2.- Image formation. |
Geometric foundations: mathematical representation of an image, basic geometric transformations, perspective transformation, parallel transformation. Illumination techniques. Color. Charge-coupled device: camera model, lens focus and perception, stereoscopic vision. |
Tema 3.- Preprocessing techniques. |
Basic relationships between pixels. Spatial domain. Frequency domain. Filtering techniques: normalization, equalization, smoothing, edge detection. |
Tema 4.- Representation techniques. |
Segmentation: detection of borders, thresholding, region growing, split and merge. Feature Extraction. |
Tema 5.- Description and recognition techniques. |
Description: border descriptors, region descriptors. Recognition. Interpretation. |
Tema 6.- Computer vision applications. |
Industrial applications: inspection, quality control. Medical applications. Office applications. |
Methodologies :: Tests |
|
Competences |
(*) Class hours
|
Hours outside the classroom
|
(**) Total hours |
Introductory activities |
|
2 |
0 |
2 |
Practicals using information and communication technologies (ICTs) in computer rooms |
|
15 |
30 |
45 |
Assignments |
|
0 |
13 |
13 |
Lecture |
|
9 |
33 |
42 |
Problem solving, classroom exercises |
|
15 |
29 |
44 |
Personal tuition |
|
2 |
0 |
2 |
|
Objective multiple-choice tests |
|
2 |
0 |
2 |
|
(*) On e-learning, hours of virtual attendance of the teacher. (**) The information in the planning table is for guidance only and does not take into account the heterogeneity of the students. |
Methodologies
|
Description |
Introductory activities |
Comprehensive description of the course: contents, assessment, etc. |
Practicals using information and communication technologies (ICTs) in computer rooms |
Practical exercises related to the theoretical concepts in lectures using standard computer vision software. |
Assignments |
Performing work related to theoretical concepts in lectures: the work will be theoretical or practical. |
Lecture |
Explanation by the teacher of Computer Vision concepts, techniques, methodologies, etc., related to the course content. |
Problem solving, classroom exercises |
Solving exercises under the supervision of the teacher. |
Personal tuition |
Personal attention by teachers of the subject. Includes personalized attention devoted to the evaluation of some projects and exercises. |
Description |
Personal attention by teachers of the subject. Includes personalized attention devoted to the evaluation of some projects and exercises. |
Methodologies |
Competences
|
Description |
Weight |
|
|
|
|
Practicals using information and communication technologies (ICTs) in computer rooms |
|
Practical exercises related to the theoretical concepts in lectures using standard computer vision software. |
50% |
Assignments |
|
Performing work related to theoretical concepts in lectures: the work will be theoretical or practical. |
25% |
Problem solving, classroom exercises |
|
Solving exercises under the supervision of the teacher. |
15% |
Objective multiple-choice tests |
|
Solve tests related to the theoretical contents of the course. |
10% |
Others |
|
|
|
|
Other comments and second exam session |
A la segona convocatòria s'hauran de tornar a realitzar les proves parcials d'avaluació continua que l'alumne no hagi aconseguit una nota minima. La nota mitjana ponderada de totes les proves parcials ha de ser com a mínim de 5. |
Basic |
Escalera, A. de la, Visión por Computador, Prentice Hall, 2001
Ajenjo, A.D, Tratamiento Digital de Imágenes, Anaya Multimedia, 1994
Forsyth, D.A.; Ponce, J., Computer vision a modern approach, Prentice Hall, 2011
Pajares Martinsanz, Gonzalo, Visión por computador: imágenes digitales y aplicaciones , Ra-Ma, 2007
|
|
Complementary |
Vitrià, J., Visió per Computador, Servei Publicacions U.A.B., 1995
Fu, K.S.; Gonzalez, R.C.; Lee, C.S.G, Robótica: Control, Detección, Visión e Inteligencia, McGraw Hill, 1990
|
|
(*)The teaching guide is the document in which the URV publishes the information about all its courses. It is a public document and cannot be modified. Only in exceptional cases can it be revised by the competent agent or duly revised so that it is in line with current legislation. |
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