Bob’s Basic Image Processing Routines

Todo

Explain DCTFeatures constructor in more detail.

(The original entry is located in /scratch/builds/bob/bob.ip.base/miniconda/conda-bld/bob.ip.base_1633535195222/_test_env_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_place/lib/python3.8/site-packages/bob/ip/base/__init__.py:docstring of bob.ip.base.DCTFeatures, line 14.)

Todo

The parameter(s) ‘levels, max_level, min_level, quantization_table’ are used, but not documented.

Parameters:

dtype : numpy.dtype

[default: numpy.uint8] The data-type for the GLCM class

glcm : bob.ip.base.GLCM

The GLCM object to use for copy-construction

(The original entry is located in /scratch/builds/bob/bob.ip.base/miniconda/conda-bld/bob.ip.base_1633535195222/_test_env_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_place/lib/python3.8/site-packages/bob/ip/base/__glcm__.py:docstring of bob.ip.base.__glcm__.GLCM, line 19.)

Todo

UPDATE as this is not true

(The original entry is located in /scratch/builds/bob/bob.ip.base/miniconda/conda-bld/bob.ip.base_1633535195222/_test_env_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_place/lib/python3.8/site-packages/bob/ip/base/__init__.py:docstring of bob.ip.base.LBPTop, line 7.)

Todo

Explain TanTriggs constructor in more detail.

(The original entry is located in /scratch/builds/bob/bob.ip.base/miniconda/conda-bld/bob.ip.base_1633535195222/_test_env_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_place/lib/python3.8/site-packages/bob/ip/base/__init__.py:docstring of bob.ip.base.TanTriggs, line 13.)

Todo

explain WeightedGaussian constructor

(The original entry is located in /scratch/builds/bob/bob.ip.base/miniconda/conda-bld/bob.ip.base_1633535195222/_test_env_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_place/lib/python3.8/site-packages/bob/ip/base/__init__.py:docstring of bob.ip.base.WeightedGaussian, line 13.)

Todo

Explain gamma correction in more detail

(The original entry is located in /scratch/builds/bob/bob.ip.base/miniconda/conda-bld/bob.ip.base_1633535195222/_test_env_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_placehold_place/lib/python3.8/site-packages/bob/ip/base/__init__.py:docstring of bob.ip.base._library.gamma_correction, line 3.)

This Python module contains base functionality from Bob bound to Python, available in the C++ counter-part bob::ip::base.

Documentation

References

Atanasoaei2012

Cosmin Atanasoaei. Multivariate Boosting with Look-up Tables for Face Processing, PhD thesis, EPFL, 2012. pdf

Sanderson2002

Conrad Sanderson and Kuldip K. Paliwal. Polynomial Features for Robust Face Authentication, In Proceedings of the IEEE International Conference on Image Processing, 2002. pdf

TanTriggs2007

Xiaoyang Tan and Bill Triggs. Enhanced Local Texture Feature Sets for Face Recognition Under Difficult Lighting Conditions, In International Conference on Analysis and Modeling of Faces and Gestures, 2007. pdf

Dalal2005

N. Dalal, B. Triggs. Histograms of Oriented Gradients for Human Detection, In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2005.

Haralick1973

R. M. Haralick, K. Shanmugam, I. Dinstein. Textural Features for Image Classification, In IEEE Transactions on Systems, Man and Cybernetics, vol. SMC-3, No. 6, p. 610-621, 1973.

Zhao2007

G. Zhao and M. Pietikainen. Dynamic Texture Recognition Using Local Binary Patterns with an Application to Facial Expressions, in IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 29, no. 6, pp. 915-928, June 2007. doi: 10.1109/TPAMI.2007.1110

Indices and tables