Knowledge-Based Intelligent Techniques in Character Recognition

Knowledge-Based Intelligent Techniques in Character Recognition presents research results on intelligent character recognition techniques, reflecting the tremendous worldwide interest in the applications of knowledge-based techniques in this challenging field. This resource will interest anyone involved in computer science, computer engineering, applied mathematics, or related fields. It will also be of use to researchers, application engineers and students who wish to develop successful character recognition systems such as those used in reading addresses in a postal routing system or processing bank checks. TOC:An Introduction to Character Recognition.- Recognition of Handwritten Digits in the Real World by a Neocognitron.- Recognition of Rotated Patterns Using Neocognitron.- Soft Computing Approach to Handwritten Numeral Recognition.- Handwritten Character Recognition Using a MLP.- Signature Verification Based on Fuzzy Genetic Algorithm.- Application of a Generic Neural Network to Handwritten Digit Classification.- High-Speed Recognition of Handwritten Amounts on Italian Checks.- Off-line Handwritten Word Recognition Using Hidden Markov Models.- Off-line Handwriting Recognition with Context Dependent Fuzzy Rules.- License-Plate Recognition.- Index.