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2 I Basic Notions

Civil administration:

Traffic analysis and control
Assessment of urban growth
Economy:
Stocks exchange forecast
Analysis of entrepreneurial performance
Engineering:
Fault detection in manufactured products
Character recognition
Speech recognition
Automatic navigation systen~s
Pollution analysis
Geology:
Classification of rocks
Estimation of mining resources
Analysis of geo-resources using satellite images
Seismic analysis
Medicine:
Analysis of electrocardiograms
Analysis of electroencephalograms
Analysis of medical images
Military:
Analysis of aerial photography
Detection and classification of radar and sonar signals
Automatic target recognition
Security:
Identification of fingerprints
Surveillance and alarm systems

As can be inferred from the above examples the pattern.; to be analysed and
recognized can be signals (e.g. e1ectrc)cardiographic signals), images (e.g. aerial
photos) or plain tables of values (e.g. stock exchange rates).

1.2 Pattern Similarity and PR Tasks

A fundamental notion in pattern recognition, independent of whatever approach we
may follow, is the notion of .similarity. We recognize two objects as being similar
because they have similarly valued common attributes. Often the similarity is
stated in a more abstract sense, not among objects but between an object and a
target concept. For instance, we recognise an object as being an apple because it
corresponds, in its features. to the idealized image, concept or prototype, we may
have of an apple, i.e., the object is similar to that concept and dissimilar from
others, for instance from an orange.