pattern recognition definition

- Pattern recognition can be defined as the categorization of input data into identifiable classes via the extraction of significant features or attributes of the data from a background of irrelevant detail.
- Duda and Hart defined it as a field concerned with machine recognition of meaningful regularities in noisy or complex environments. A more simple definition is search for structure in data.
The design of a pattern recognition system essentially involves the following thr eeaspects:
- Data representation,
- Classification
- finally, Prototyping.
The problem domain dictates the choice of sensors, pre-processing techniques, representation scheme, and decision making model.
i. Representation - It describes the patterns to be recognized;
ii. Classification - It recognizes the “category” to which the patterns provided belong to;
iii. Prototyping - It is the mechanism used for developing the prototypes or models.
Prototypes are used for representing the different classes to be recognized.
A general pattern recognition system is shown in the Figure 1.1.
In the first step data is acquired and preprocessed, this step is followed by feature extraction, feature reduction and grouping of features, and finally the features are classified.
In the classification step, the trained classifier assigns the input pattern to one of the pattern classes based on the measured features. The training set used during construction of the classifier is different from the test set which is used for evaluation. This ensures different performance environment.