Pattern Recognition

The practice of recognizing patterns and classifying data accordingly, has prevailed for a long time and human beings have taken long strides in this field in recent times. Classifying information observed from nature was practiced even by the Stone Age man. He used different patterns to identify plants, animals and other elements of nature. The difference between those times and that of today is the availability of high tech instruments. Today, it is possible to store huge amount of data in computers. Thus, the field of pattern recognition has developed at a fast pace.

The field of research activity, in which observations being made are classified and described, is known as pattern recognition. It is one of the applications of artificial intelligence. If statistical information obtained from patterns is used in their classification, the method is known as statistical pattern recognition. The statistical pattern recognition methodology is sub-divided into other disciplines such as feature extraction, discriminant analysis, cluster analysis and error estimation. The syntactical pattern recognition methodology carries out grammatical parsing and inference. The pattern recognition methods are often used in identifying data that is very complicated. Therefore, this identification system can fall in the group of algorithmic modeling.

Prior knowledge of the patterns, instead of just obtaining statistical data, should also prove to be useful in classifying them. There are basically three steps/activities involved in pattern recognition system. First activity is the reception of observations or data by means of sensors. These pattern recognition receptors/sensors gather information to be classified. Computation of numerical data and symbolic information is carried out by means of a mechanism called feature extraction. The information that is gathered and then extracted in these two steps is finally classified.

Pattern Recognition and Machine Learning
The pattern recognition system is one of the branches of artificial intelligence. In the different artificial intelligence programs, machine learning helps in carrying out pattern recognition. One of the examples/applications of using pattern recognition and machine learning is statistical data mining. In the process of machine learning, a computer is provided instructions as to how a particular task should be carried out. The process of machine learning is implemented in two different ways i.e. through supervised and unsupervised learning.

Supervised Learning: In supervised learning, the computer to be taught is provided with pattern recognition algorithms. Different examples about how to complete a particular task are presented to the computer. These examples show how the process of completing a task is executed. It also gives information about the product. Throughout the process of training/teaching the computer, feedback is also provided.

Unsupervised Learning: In unsupervised learning, the computer doesn't get any feedback or guidance while learning. No guidelines are provided either. It means that unlike supervised learning, patterns are not labeled or classified beforehand. The process of classifying information created by the artificial intelligence program thus, needs to be very efficient.

Other Applications of Pattern Recognition
Applications such as computer-aided diagnosis (CAD) makes use of pattern recognition software. Other applications include classifying a particular text in different categories like speech recognition, recognizing handwriting, industrial inspection, person identification, etc.

Image Analysis
The use of pattern recognition in image analysis proves to be of great help. One of the important image analysis tools used by computers is the neural networks. The neural network and other tools like edge detectors, which are based on the model of human visual perception can be used in the process of image analysis.

Pattern Recognition Tests
The different types of pattern recognition tests can be used in measuring the aptitude of a person. One gets an indication of IQ with such tests. The questions presented in such tests require us to recognize the pattern hidden in the given design, set of numbers, etc.

The concept of pattern recognition has lot many applications. Due to the progress shown by many such concepts and techniques, the artificial intelligence's future seems bright. This technique of recognizing the category/class of a particular object helps us identify and describe it easily and in no time.