1. Contourlet Transforms For Feature Detection
Wei-shi Tsai
April 29th, 2008

2. Feature Detection Focus will be on edge detection
Gradient operators (Sobel, Roberts)
Laplacian operators
LoG (Laplacian of Gaussian)
DoG (Difference of Gaussians)
Canny method
Anisotropic diffusion

3. Contourlets (Do and Vetterli, 2005)
Captures smooth contours and edges at any orientation
Filters noise
Derived directly from discrete domain instead of extending from continuous domain
Can be implemented using filter banks

4. Contourlet filter bank
The transform decouples the multiscale and the directional decompositions.

5. Test Pattern Image – Scale 1

6. Test Pattern Image – Scale 2

7. Peppers Image – Scale 1

8. Peppers Image – Scale 2

9. Generic Girl Image – Scale 1

10. Generic Girl Image – Scale 2

11. Tiffany Image – Scale 1

12. Tiffany Image – Scale 2

13. Elaine Image – Scale 1

14. Elaine Image – Scale 2

15. Lena Image – Scale 1

16. Lena Image – Scale 2

17. Conclusions Contourlet transforms can be used for edge detection
Results can vary based on the type of image
Evaluation is only useful given what the feature extracted is to be used