13-08-2012, 02:31 PM
pattern recognition
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INTRODUCTION
• This course deals with pattern recognition. A pattern is either a
physical object, for example a book or a chair or an abstract notion,
like style of talking, or style of writing. It is also a shared property of a
set of objects; for example, chairs, rectangles, or blue colored objects.
We illustrate using ellipses and rectangles shown in Figure 1.
Figure 1: Ellipses and Rectangles
Cognition is the act of seeing or perceiving, whereas recognition
means as having seen or perceived. There are three ways of appreciating
the activity of pattern recognition in a simple manner:
1. Classification: Assign a pattern to one of the already known (se-
mantically labelled) classes. For example, consider the two classes
of physical objects shown in Figure 1: ellipses and rectangles where
ellipse and rectangle are class labels. Now the classification prob-
lem, prominent in pattern recognition, involves:
(a) Either learn a model or directly use the training data set
(collection of labelled patterns) and
(b) assign a class label to a new pattern (test pattern) or equiv-
alently assign the test pattern to one of the known classes.
That is, with respect to objects in Figure 1, given a new
object we would like to classify it as either an ellipse or a
rectangle.