Department of Information and Computing Sciences

Departement Informatica Onderwijs
Bachelor Informatica Informatiekunde Kunstmatige intelligentie Master Computing Science Game&Media Technology Artifical Intelligence Business Informatics

Onderwijs Informatica en Informatiekunde

Vak-informatie Informatica en Informatiekunde

Beeldverwerking

Website:website met extra informatie
Vakcode:INFOIBV
Studiepunten:7.5 ECTS
Periode:periode 1 (week 36 t/m 45, d.w.z. 4-9-2017 t/m 10-11-2017; herkansing week 1)
Timeslot:D256
Deelnemers:tot nu toe 102 inschrijvingen
Rooster:De officiële roosters staan ook in Osiris
Docenten:
vormgroeptijdweekzaaldocent
college   wo 15.15-17.0037-39 RUPPERT-042 Debabrata Panja
Ronald Poppe
   
40 EDUC-MEGARON
41-44 RUPPERT-042
vr 11.00-12.4536 RUPPERT-ROOD
37-44 RUPPERT-042
practicum          Federico D'Ambrosio
 
groep 1 vr 9.00-10.4537-44 BBG-109 CLZ Sander Vanheste
 
groep 2 vr 9.00-10.4537-44 BBG-175 CLZ Daphne Odekerken
 
groep 3 vr 9.00-10.4537-44 BBG-103 CLZ Ruben Schenkhuizen
 
Tentamen:
week: 45vr 10-11-20178.30-10.30 uurzaal: EDUC-BETA
week: 1vr 5-1-20188.30-10.30 uurzaal: EDUC-THEATRONaanvullende toets
Inhoud:Image Processing provides basic knowledge and skills for the analysis and processing of digital images. We discuss fundamental and core techniques such as filters, edges, colors and spectral techniques. We also treat advanced topics including corner detection, Fourier shape descriptors and automatic thresholding. The course will be in English. The assignments are mandatory and require (basic) C# skills. Course goals:
  • Knowledge of:
    • Ways of describing images, including histograms
    • Linear/non-linear filters and morphological filters
    • Image processing tasks including edge and curve detection and automatic thresholding
    • Spectral techniques and the relation between continuous and discrete
    • Color spaces and their relations
    • Shape descriptors, including Fourier shape descriptors
  • Experience with:
    • Designing and deriving filters to enhance images or extract features
    • Applying filters, including morphological filters
    • Designing image processing pipelines
Literatuur:"Principles of Digital Image Processing" by Burger & Burge. It consists of three volumes, which can be downloaded from SpingerLink (free of charge if you access the pages through the UU domain): We will also use "Advanced Engineering Mathematics (10th Edition)" by Erwin Kreyszig (Chapter 11), for which we will provide the material.
Werkvorm:Lectures (15)
Exercise sessions (2)
Assignments (3) in pairs (mandatory)
Exam and mid-term exam (mandatory)
Toetsvorm:The mid-term (M) exam counts for 20%, the final (E) exam for 30%. The two first assignments (A1,A2) count for 10% each, while the final assignment (A3) makes up 30% of the final grade. To pass the course, the weighted average of the exams and the weighted average of the assignments should both be at least 4. The final grade should be at least 5.5.
Inspanningsverplichting voor aanvullende toets:You can either re-take the mid-term exam or the final exam. Your original grade for that exam should be at least 4.
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