Pattern recognition algorithms – Literature Review

I post a draft Literature Review on the Pattern Recognition subject.

The literacy review is focused on supervised training algorithms that compute stil images. It contains some techniques/models for image pre-processing (using RBG band color, input sample dimensionality reducers and log-polar image representation), features extractors (affine invariant Wavelet functions, colour channel coupling and multiple sized window texture recognition), classifiers (firstly a Probability Density Function theorem is introduced then a fast k-Nearest Neighbor approximation algorithm) and training (weighting imbalanced training set).

Here the PDF version: Pattern Recognition – LiteratureReview v0.1.