A REVIEW ON PATTERN RECOGNITION MODELS

Pattern Recognition is widely used in many fields of computer science and medical science. It is one of artificial intelligence's actively searched and very important branches. It can be called a science that attempts to develop machines as smart as humans for recognizing patterns and then categorizing in a reliable and simple way into desired categories. In the last few decades, researches attention has been grabbed by pattern recognition as an approach of learning because it has wide areas of application. Its applications include drug, information systems, automation, data mining, military intelligence, document classification, bioinformatics, business, speech recognition, and several others. Various approaches to Pattern Recognition have been presented in this review paper and their pros-cons have shown the application of a specific paradigm. Depending on the surevy, the techniques of pattern recognition are categorized in six parts. They are Structural Techniques, Statistical Techniques, Neural Network Approach, Template Matching, Hybrid Models and Fuzzy Model.