1. Lecture 3. Edge Detection, Texture
Computer Vision
Lecture 3. Edge Detection, Texture
Oleh Tretiak © 2005

2. Lecture Outline Noise and Filtering, 8.1-8.2 Edge Detection 8.3, 8.3.1
Texture - what is it?
Filter banks for texture detection 9.1
LaPlacian pyramid and texture analysis
Oleh Tretiak © 2005

3. White Gaussian Noise
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4. Effect of Filters on Noise
White noise convolved with Gaussian filter. r is a parameter proportional to the width of the filter. Noise standard deviation  decreases with increasing r.
r = 2,  = 6.25
r = 4,  = 3.7
r = 5,  = 3.1
r = 3,  = 4.65
Oleh Tretiak © 2005

5. Gaussian Edge Detection
Step change of 10 with
noise,  = 25.
Differentiation cannot
detect the edges.
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6. Gaussian Edge Detection
Step plus noise after
Gaussian filter
Laplacian filter applied
to image on left
Horizontal derivative
applied to image on left
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7. Laplacian Edge Detection
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8. Gaussian Pyramid
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9. What is Texture?
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10. Natural Textures
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11. Texture Filters
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12. Application of Texture Filters
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13. Periodicity in Texture
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14. Periodicity?
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15. Gabor Filters
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16. Laplacian Pyramid
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