20-11-2012, 03:16 PM
Pattern Recognition
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Two Schools of Thought
Statistical Pattern Recognition
The data is reduced to vectors of numbers
and statistical techniques are used for
the tasks to be performed.
2. Structural Pattern Recognition
The data is converted to a discrete structure
(such as a grammar or a graph) and the
techniques are related to computer science
subjects (such as parsing and graph matching).
Classification in Statistical PR
A class is a set of objects having some important
properties in common
A feature extractor is a program that inputs the
data (image) and extracts features that can be
used in classification.
A classifier is a program that inputs the feature
vector and assigns it to one of a set of designated
classes or to the “reject” class.
Some Terminology
Classes: set of m known categories of objects
(a) might have a known description for each
(b) might have a set of samples for each
Reject Class:
a generic class for objects not in any of
the designated known classes
Classifier:
Assigns object to a class based on features
Classification using nearest class mean
Compute the Euclidean distance between feature vector X and the mean of each class.
Choose closest class, if close enough (reject otherwise)