Printed and Handwritten Document Analysis: A Machine Learning Perspective Hardcover

This reference book presents the fundamentals of machine learning tools commonly used by researchers. The book includes graphical models like Bayesian networks and hidden Markov models with wider application potentials in the document analysis area. It also covers distributions that have not yet been used, such as circular distributions with potential use in handwriting recognition and in color scene text image segmentation. The book also details which—and how—these machine learning tools are useful at different stages. A full chapter is devoted to online handwriting recognition