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In this paper, we propose a framework for defining feature extraction techniques, called Pixel Clustering. It is an extension of feature extraction with Wavelets. We propose two linear feature extraction techniques using Pixel Clustering: IntensityPatches and RegionPatches. We assess the methods in color and grayscale image datasets: two face datasets and two object datasets. The proposed methods...
This work proposes a theoretical framework for an unsupervised feature extraction called Pixel Clustering. The main idea is based on the clustering of the pixels in order to mitigate the multicollinearity issue and a new feature is extracted for each cluster of similar pixels. This allows to define feature extraction techniques by setting just three parts: (1) defining pixel vectors in the training...
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