contourlet transforms for feature detection
DESCRIPTION
Contourlet Transforms For Feature Detection. Wei-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. - PowerPoint PPT PresentationTRANSCRIPT
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