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I have read all possible articles on gabor functions but they did not lead me to anything useful. Could someone briefly explain whether there is a difference between the two ?
Which of the above two is used in image classification ?
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Gabor filters are used as detectors of small, localized cloud stretches or blobs in the satellite image. As these detectors are localized, a large number of Gabor filters are used to cover the whole image (the exact number depends on the size of the image and the size of each filter's receptive field).
In image processing, a Gabor filter, named after Dennis Gabor, is a linear filter used for texture analysis, which essentially means that it analyzes whether there is any specific frequency content in the image in specific directions in a localized region around the point or region of analysis.
Gabor wavelet filters are popularly used in many applications of image processing such as extraction of edges, texture analysis, object recognition, and many more. Local spatial as well as frequency information can be obtained by the use of Gabor wavelet filters.
Gabor filter is used to capture facial features aligned at specific angles. Along with these, a Binary Particle Swarm Optimization based feature selection algorithm is used to search the feature space for the optimal feature subset.
I would provide you certain links that would make you clear about the concept of GABOR TRANSFORM as well as GABOR FILTERS
here
here
here
here
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The Gabor transform is a one-dimensional transform used for analysing 1d signals (such as audio data).
Gabor filters are two-dimensional generalisations of the Gabor transform used for analysing 2d signals (such as image data).
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