Functions | Variables
texture_features Namespace Reference

Functions

def eigen_texture
 calculates eigen values of covariance matrix accumulating statistics of sobel filter responses in an image block
def visualize

Variables

tuple eig_tex_np = eigen_texture(im, blocksize=s, filtersize=3)
tuple im = hg.cvLoadImage('/home/haidai/svn/robot1/src/projects/08_03_dog_commands/dragonfly_color_calibration/untitled folder/camera_image.png')
tuple s = (i+1)

Function Documentation

def texture_features.eigen_texture (   cv_image,
  blocksize = 8,
  filtersize = 3 
)

calculates eigen values of covariance matrix accumulating statistics of sobel filter responses in an image block

Parameters:
cv_imageopencv image to calculate texture over
blocksizesize of block to accumulate statistics (in pixels)
filtersizesize of sobel filter to use (in pixels)
Returns:
numpy matrix of size (width, height, 2) where [:,:,0] is the set of first eigen values and [:,:,1] is the second set

Definition at line 42 of file texture_features.py.

def texture_features.visualize (   eigens)

Definition at line 53 of file texture_features.py.


Variable Documentation

tuple texture_features::eig_tex_np = eigen_texture(im, blocksize=s, filtersize=3)

Definition at line 85 of file texture_features.py.

tuple texture_features::im = hg.cvLoadImage('/home/haidai/svn/robot1/src/projects/08_03_dog_commands/dragonfly_color_calibration/untitled folder/camera_image.png')

Definition at line 80 of file texture_features.py.

tuple texture_features::s = (i+1)

Definition at line 83 of file texture_features.py.



clutter_segmentation
Author(s): Jason Okerman, Martin Schuster, Advisors: Prof. Charlie Kemp and Jim Regh, Lab: Healthcare Robotics Lab at Georgia Tech
autogenerated on Wed Nov 27 2013 12:07:16