Linear Algebra Techniques For Pattern Recognition: Feature Extraction Case Studies
David P. Casasent · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1983
Many linear algebra operations, matrix inversions, etc. are required in pattern recognition as well as in signal processing. In this paper, we concentrate on feature extraction pattern recognition techniques (specifically a chord distribution and a moment feature space). For these two case studies, we note the various linear algebra operations required in distortion-invariant pattern recognition. Systolic processors can easily perform all reauired linear algebra functions.