A general purpose rotation, scaling, and translation invariant pattern classification system

Abstract

Artificial neural networks have recently been used for pattern classification purposes. In this work, a general purpose pattern classification system which is rotation, scaling, and, translation invariant is introduced. The system has three main blocks; a Karhunen-Loeve transformation based preprocessor, an artificial neural network based classifier, and an interpreter. Through experimentation on the English alphabet, the Japanese Katakana alphabet, and some geometric symbols the power of the system in maintaining invariancies and performing pattern classification has been shown.