Handwriting Recognition / Soft Computing and Probabilistic Approaches | Handwriting Recognition: Soft Computing and Probabilistic Approaches

Handwriting Recognition: Soft Computing and Probabilistic Approaches

Overview

This book offers a novel perspective on unconstrained handwriting recognition, introducing advanced techniques for identifying written words and characters. It delves into the complexities of uncertainties and variations inherent in handwriting data. The text presents algorithms that employ modified hidden Markov models and Markov random field models to statistically and structurally represent handwriting within a unified framework. Methods utilizing fuzzy logic and fuzzy sets for recognition are also explored, with their efficacy validated through extensive experimental data.

Who it's for

• Researchers and practitioners in pattern recognition and artificial intelligence.
• Students and professionals interested in machine learning and data analysis.
• Individuals working with character and word recognition systems.

Key features

• Binding: Hardback
• Pages: 245
• Publisher: Springer
• Year: 2003
• ISBN: 9783540401773
• Dimensions: 156x234 mm