Wednesday, February 4, 2009

Orientation and the Gabor Filter

To examine orientation as saliency channel, we adopted the model proposed by Itti et al, wherein a Gabor Filter is applied to the image. The Gabor Filter uses a 2D Gabor function (a sinusoid multiplied by a Gaussian kernel) as its impulse response. This can roughly be visualized as:
1D
2D

Note the size and ellipticity of the Gabor function, and standard deviation of the Gaussian are variable.

The filter then applies this function to the image, emphasizing edges along the rotation of the Gaussian envelope.

Below are several examples of applying different orientations of the Gabor function to an image.

pi/4
pi/2
3pi/4
pi


Note a wavelength of 10 and a circular (ellipticity = 1) are used with a StD of ~5.6.

Each orientation map is created in the usual way, by taking differences of several scales of the filtered image.

J Movellan, Tutorial on Gabor Filters
OpenCV implementation: http://www.personal.reading.ac.uk/~sir02mz/CGabor/example.html
Posted by Stat Zombie at 12:13 PM
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12 comments:

  1. How to speed up the convolution ?

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  2. how to find out in which direction the max response output is obtained using Gabor filter?

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