Extract DCT coefficients
Algorithms have at least one input and one output. All algorithm endpoints are organized in groups. Groups are used by the platform to indicate which inputs and outputs are synchronized together. The first group is automatically synchronized with the channel defined by the block in which the algorithm is deployed.
Parameters allow users to change the configuration of an algorithm when scheduling an experiment
|block-overlap||Number of pixels to overlap (in both directions)||uint32||11|
|number-of-components||Number of components kept. Is n-1 since the DC component is excluded||uint32||45|
|norm-dcts||For a set of blocks, will normalize the coefficients||bool||True|
|block-size||Size of the block in pixels (in both directions)||uint32||12|
|norm-blocks||Will normalize the pixels in the block before the DCT computation||bool||True|
The code for this algorithm in Python
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This algorithm relies on the Bob library.
The input, image, is a two-dimensional array of floats (64 bits) corresponding to one image. The outputs, features, is a two-dimensional array of floats (64 bits) corresponding to the DCT coeficients of each block.
|[McCool2009]||McCool, Christopher, and Sébastien Marcel: Parts-based face verification using local frequency bands. Advances in Biometrics. Springer Berlin Heidelberg, 2009. 259-268.|
|[McCool2013]||McCool, Christopher, et al. &quot;Session variability modelling for face authentication.&quot; IET biometrics 2.3 (2013): 117-129.|