Abstract
Feature extraction is a critical step in any pattern classification system. In order for the pattern recognition process to be tractable, it is necessary to convert patterns into features, which are condensed representations of the patterns, containing only salient information. Features contain the characteristics of a pattern in a comparable form making the pattern classification possible. The extraction of “good” features from the signal patterns and the selection from them of the ones with the most discriminatory power is very crucial for the success of the classification process. The feature extraction and selection is a dimensionality reduction process that is necessary in order to meet software and hardware constraints.
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Christodoulou, C.I., Kyriacou, E., Pattichis, M.S., Pattichis, C.S. (2011). Plaque Feature Extraction. In: Nicolaides, A., Beach, K., Kyriacou, E., Pattichis, C. (eds) Ultrasound and Carotid Bifurcation Atherosclerosis. Springer, London. https://doi.org/10.1007/978-1-84882-688-5_14
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