ACV_Slides at Fachhochschule St. Pölten

Flashcards and summaries for ACV_Slides at the Fachhochschule St. Pölten

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Exemplary flashcards for ACV_Slides at the Fachhochschule St. Pölten on StudySmarter:

What should be considered for image subtraction?

Exemplary flashcards for ACV_Slides at the Fachhochschule St. Pölten on StudySmarter:

What is the plenoptic function?

Exemplary flashcards for ACV_Slides at the Fachhochschule St. Pölten on StudySmarter:

What does a color image consist of?

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Exemplary flashcards for ACV_Slides at the Fachhochschule St. Pölten on StudySmarter:

What are challanges in computer vision?

Exemplary flashcards for ACV_Slides at the Fachhochschule St. Pölten on StudySmarter:

What do you get with f(x,y) in image processing?

Exemplary flashcards for ACV_Slides at the Fachhochschule St. Pölten on StudySmarter:

How does image multiplication work?

Exemplary flashcards for ACV_Slides at the Fachhochschule St. Pölten on StudySmarter:

Explain the image division?

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Exemplary flashcards for ACV_Slides at the Fachhochschule St. Pölten on StudySmarter:

Nenne Besonderheiten von logischen Operationen?

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Are there another types of images?

Exemplary flashcards for ACV_Slides at the Fachhochschule St. Pölten on StudySmarter:

Was ist ein normalisiertes Histogramm?

Exemplary flashcards for ACV_Slides at the Fachhochschule St. Pölten on StudySmarter:

Wie kann man Bewegungen in einer Videosequenz entfernen?

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Exemplary flashcards for ACV_Slides at the Fachhochschule St. Pölten on StudySmarter:

Was machen die logischen Operationen AND, OR und XOR einfach ausgedrückt?

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Exemplary flashcards for ACV_Slides at the Fachhochschule St. Pölten on StudySmarter:

ACV_Slides

What should be considered for image subtraction?

You should use the absolute values, otherwise negative values are possible

ACV_Slides

What is the plenoptic function?

Is an idealized function in the CV to describe an image independent of the position of the viewer.

ACV_Slides

What does a color image consist of?

3 gray value images (image with 3 Layers)

ACV_Slides

What are challanges in computer vision?

  1. view point (Betrachtungswinkel)
  2. illumination (Ausleuchtung)
  3. occlusion (Verdeckung)
  4. scale (Größenverhältnisse)
  5. deformation (Verformung)
  6. background clutter (Unordnung im Hintergrund)
  7. object intra-class variation (objektinterne Klassenvariation)
  8. local ambiguity (lokale Mehrdeutigkeit)
  9. the world behind the image (Aussagekraft)

ACV_Slides

What do you get with f(x,y) in image processing?

It gives the intensity at position (x,y)

ACV_Slides

How does image multiplication work?

Multiplication of the gray values by a constant factor C.


C>1: Image becomes brighter (possibly clipping), 

C<1: Image becomes darker

! Histogram-based approaches are better for brightness correction

ACV_Slides

Explain the image division?

Used for change detection (as in subtraction), 


Unchanged regions :value 1


Changed regions: 

im1> im2 = [1 255]

im1<im2 = [0 1]

ACV_Slides

Nenne Besonderheiten von logischen Operationen?

  • Pixelweise logische Verknüpfung von Grauwerten
  • Nur sinnvoll auf Binärbildern
  • Bilder vorher ev. invertieren damit Hintergrund = 0 und       Vordergrund = 1

ACV_Slides

Are there another types of images?

Multispectral images (for different IR band)

ACV_Slides

Was ist ein normalisiertes Histogramm?

Normalisiertes Histogramm stellt Auftrittswahrscheinlichkeiten der Grauwerte dar. Normalisierungsfaktor = Anzahl der Pixel

ACV_Slides

Wie kann man Bewegungen in einer Videosequenz entfernen?

Durch die Bildmittelung. Kleine Bewegungen setzen sich im Mittelwertbild nicht durch!

ACV_Slides

Was machen die logischen Operationen AND, OR und XOR einfach ausgedrückt?

AND =  zeigt an was in beiden Bildern gleich ist (nur doppelte)

OR = zeigt alles von beiden Bildern an (alle)

XOR = zeigt an was nur einmal vorkommt (keine doppelten)

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