Contourlet Transforms For Feature Detection

Contourlet Transforms For Feature DetectionWei-shi Tsai

April 29th, 2008

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

Contourlets (Do and Vetterli, 2005)

Captures smooth contours and edges at any orientation

Filters noiseDerived directly from discrete domain

instead of extending from continuous domain

Can be implemented using filter banks

Contourlet filter bank

The transform decouples the multiscale and the directional decompositions.

Test Pattern Image – Scale 1

Test Pattern Image – Scale 2

Peppers Image – Scale 1

Peppers Image – Scale 2

Generic Girl Image – Scale 1

Generic Girl Image – Scale 2

Tiffany Image – Scale 1

Tiffany Image – Scale 2

Elaine Image – Scale 1

Elaine Image – Scale 2

Lena Image – Scale 1

Lena Image – Scale 2

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