Project repository for the course pattern recognition at TEC
eigenFaces uses PCA to find the axis that contains the most valuable information and then reduces the dimensionalitty of the problem by projecting the images in to a new space generated by the eigen-vectors with the biggest eigen-values
opticalFlow uses a traditional approach by calculating the change in pixels en a series of frames.
binaryClasification uses the perceptron algorithm and Fisher's discriminant to defferentiate two classes.
convolutionAndFilters contain the implementation of various filters and the implementation of a convolution function.
imageSegmentationKittler uses Kittler's algorithm to segment cell images