This project was done as part of the requirements for a Pattern Recognition course (308-644B) at McGill University. Course information and contents are available on the web. Also, here is a shortcut to the General and Specific Links assembled for Pattern Recognition .
Pattern recognition is concerned with analyzing scenes in the real world in order to come up with a high level description of such scenes to facilitate the automation of certain tasks. For example, in postal mail processing applications, machines that can recognize addresses on letters and packages would certainly be more efficient at sorting these mail items than human operators thus improving the mail service to the public.
Any machine with pattern recognition capabilities usually involves an image acquisition stage followed by some preprocessing to prepare the scene (pattern) for classification. Following that, features of the pattern are extracted and input to what is called a classifier. The classifier outputs a decision concerning the input pattern. For example, the classifier may decide that the input character was an 'E'.