28 November 1983 Linear Algebra Techniques For Pattern Recognition: Feature Extraction Case Studies
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Abstract
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.
© (1983) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
David Casasent, David Casasent, } "Linear Algebra Techniques For Pattern Recognition: Feature Extraction Case Studies", Proc. SPIE 0431, Real-Time Signal Processing VI, (28 November 1983); doi: 10.1117/12.936466; https://doi.org/10.1117/12.936466
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