Extract DCT coefficients

This algorithm is a legacy one. The API has changed since its implementation. New versions and forks will need to be updated.
This algorithm is splittable

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.

Group: main

Endpoint Name Data Format Nature
image system/array_2d_floats/1 Input
features system/array_2d_floats/1 Output

Parameters allow users to change the configuration of an algorithm when scheduling an experiment

Name Description Type Default Range/Choices
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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Extract DCT features for the parts-based Face Recognition System described in [McCool2009], [McCool2013].

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 S├ębastien Marcel: Parts-based face verification using local frequency bands. Advances in Biometrics. Springer Berlin Heidelberg, 2009. 259-268.
[McCool2013]McCool, Christopher, et al. "Session variability modelling for face authentication." IET biometrics 2.3 (2013): 117-129.


Updated Name Databases/Protocols Analyzers
tpereira/tpereira/full_isv/2/btas2015_periocular_mobio-female_det_bobv2-0 mobio/1@female tutorial/eerhter_postperf_iso/1

This table shows the number of times this algorithm has been successfully run using the given environment. Note this does not provide sufficient information to evaluate if the algorithm will run when submitted to different conditions.

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