ROTATION-INVARIANT PATTERN RECOGNITION USING OPTIMUM FEATURE EXTRACTION

Autor:	Ronald Wu, Henry Stark
Rok vydání:	1986
Předmět:	Transformation (function) Computer science business.industry Orientation (geometry) Statistical pattern Feature extraction Pattern recognition Artificial intelligence business Rotation (mathematics) Invariant pattern recognition
DOI:	10.1016/b978-0-444-87877-9.50037-6
Popis:	In this paper we consider the problem of detecting a target regardless of its orientation when it is known that the target must be from one of two classes. We assume significant random intraclass variability, a complication which requires techniques from statistical pattern recognition for amelioration. The Foley-Sammon transformation for selecting optimum features from random training samples is used to solve the problem.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::f7db41dac42251adcdf5eb4d2945b8c2 https://doi.org/10.1016/b978-0-444-87877-9.50037-6 Zobrazit plný text záznamu