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Pattern recognition
 
 
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Pattern recognition is a sub-topic of machine learning
Machine learning

Machine learning is the subfield of artificial intelligence that is concerned with the design and development of algorithms that allow computers to improve their performance over time based on data, such as from sensor data or databases....
. It is "the act of taking in raw data and taking an action based on the category of the data". Most research in pattern recognition is about methods for supervised learning
Supervised learning

Supervised learning is a machine learning technique for learning a function from training data. The training set consist of pairs of input objects , and desired outputs....
 and unsupervised learning
Unsupervised learning

In machine learning, unsupervised learning is a class of problems in which one seeks to determine how the data are organized. It is distinguished from supervised learning in that the learner is given only unlabeled examples....
.

Pattern recognition aims to classify data
DATA

Debt, AIDS, Trade in Africa is a multinational Non-governmental organization founded in January 2002 in London by U2's Bono along with Robert Sargent Shriver III and activists from the Jubilee 2000 Drop the Debt campaign....
 (pattern
Pattern

A pattern, from the French language patron, is a type of theme of recurring events of or objects, sometimes referred to as elements of a set....
s) based either on a priori
A priori and a posteriori (philosophy)

The terms "a priori" and "a posteriori" are used in philosophy to distinguish two types of knowledge, justifications or arguments....
 knowledge or on statistical
Statistics

Statistics is a Mathematics pertaining to the collection, analysis, interpretation or explanation, and presentation of data. It also provides tools for prediction and forecasting based on data....
 information extracted from the patterns. The patterns to be classified are usually groups of measurements or observations, defining points in an appropriate multidimensional space.






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Pattern recognition is a sub-topic of machine learning
Machine learning

Machine learning is the subfield of artificial intelligence that is concerned with the design and development of algorithms that allow computers to improve their performance over time based on data, such as from sensor data or databases....
. It is "the act of taking in raw data and taking an action based on the category of the data". Most research in pattern recognition is about methods for supervised learning
Supervised learning

Supervised learning is a machine learning technique for learning a function from training data. The training set consist of pairs of input objects , and desired outputs....
 and unsupervised learning
Unsupervised learning

In machine learning, unsupervised learning is a class of problems in which one seeks to determine how the data are organized. It is distinguished from supervised learning in that the learner is given only unlabeled examples....
.

Pattern recognition aims to classify data
DATA

Debt, AIDS, Trade in Africa is a multinational Non-governmental organization founded in January 2002 in London by U2's Bono along with Robert Sargent Shriver III and activists from the Jubilee 2000 Drop the Debt campaign....
 (pattern
Pattern

A pattern, from the French language patron, is a type of theme of recurring events of or objects, sometimes referred to as elements of a set....
s) based either on a priori
A priori and a posteriori (philosophy)

The terms "a priori" and "a posteriori" are used in philosophy to distinguish two types of knowledge, justifications or arguments....
 knowledge or on statistical
Statistics

Statistics is a Mathematics pertaining to the collection, analysis, interpretation or explanation, and presentation of data. It also provides tools for prediction and forecasting based on data....
 information extracted from the patterns. The patterns to be classified are usually groups of measurements or observations, defining points in an appropriate multidimensional space. This is in contrast to pattern matching
Pattern matching

In computer science, pattern matching is the act of checking for the presence of the constituents of a given pattern. In contrast to pattern recognition, the pattern is rigidly specified....
, where the pattern is rigidly specified.

Overview

A complete pattern recognition system consists of a sensor
Sensor

A sensor is a device that measures a physical quantity and converts it into a signal which can be read by an observer or by an instrument. For example, a mercury thermometer converts the measured temperature into expansion and contraction of a liquid which can be read on a calibrated glass tube....
 that gathers the observations to be classified or described, a feature extraction
Feature extraction

In pattern recognition and in , Feature extraction is a special form of dimensionality reduction.When the input data to an algorithm is too large to be processed and it is suspected to be notoriously redundant then the input data will be transformed into a reduced representation set of features ....
 mechanism that computes numeric or symbolic information from the observations, and a classification
Statistical classification

Statistical classification is a procedure in which individual items are placed into groups based on quantitative information on one or more characteristics inherent in the items and based on a training set of previously labeled items....
 or description scheme that does the actual job of classifying or describing observations, relying on the extracted features.

The classification or description scheme is usually based on the availability of a set of patterns that have already been classified or described. This set of patterns is termed the training set
Training set

In artificial intelligence, a training set consists of an input array and an answer vector, and is used together with a supervised learning method to train a knowledge database used by an AI machine....
, and the resulting learning strategy is characterized as supervised learning
Supervised learning

Supervised learning is a machine learning technique for learning a function from training data. The training set consist of pairs of input objects , and desired outputs....
. Learning can also be unsupervised
Unsupervised learning

In machine learning, unsupervised learning is a class of problems in which one seeks to determine how the data are organized. It is distinguished from supervised learning in that the learner is given only unlabeled examples....
, in the sense that the system is not given an a priori labeling of patterns, instead it itself establishes the classes based on the statistical regularities of the patterns.

The classification or description scheme usually uses one of the following approaches: statistical
Statistical classification

Statistical classification is a procedure in which individual items are placed into groups based on quantitative information on one or more characteristics inherent in the items and based on a training set of previously labeled items....
 (or decision theoretic) or syntactic
Syntactic pattern recognition

Syntactic pattern recognition or structural pattern recognition is a form of pattern recognition, where items are presented pattern structures which can take into account more complex interrelationships between features than simple numerical feature vectors used in statistical classification....
 (or structural). Statistical pattern recognition is based on statistical characterizations of patterns, assuming that the patterns are generated by a probabilistic system. Syntactical (or structural) pattern recognition is based on the structural interrelationships of features. A wide range of algorithms can be applied for pattern recognition, from very simple Bayesian classifiers
Naive Bayes classifier

A naive Bayes classifier is a term in Bayesian statistics statistics dealing with a simple probabilistic Classifier based on applying Bayes' theorem with strong statistical independence assumptions....
 to much more powerful neural networks
Artificial neural network

An artificial neural network , often just called a "neural network" , is a mathematical model or computational model based on biological neural networks....
.

An intriguing problem in pattern recognition is the relationship between the problem to be solved (data to be classified) and the performance of various pattern recognition algorithms (classifiers). Van der Walt and Barnard (see reference section) investigated very specific artificial data sets to determine conditions under which certain classifiers perform better and worse than others.

Pattern recognition is more complex when templates are used to generate variants. For example, in English, sentences often follow the "N-VP" (noun - verb phrase) pattern, but some knowledge of the English language is required to detect the pattern. Pattern recognition is studied in many fields, including psychology
Psychology

Psychology is an academic and applied science discipline involving the science study of human mental functions and behavior. Occasionally it also relies on symbolic hermeneutics and critical theory, although these traditions are less pronounced than in other social sciences such as sociology....
, ethology
Ethology

Ethology is the scientific study of animal behavior, and a branch of zoology .Although many naturalists have studied aspects of animal behavior through the centuries, the modern discipline of ethology is usually considered to have arisen with the work in the 1930s of Dutch biologist Nikolaas Tinbergen and Austrian biologist Konrad Lorenz,...
, cognitive science
Cognitive science

Cognitive science may be concisely defined as the study of the nature of intelligence. It draws on multiple empirical disciplines, including psychology, philosophy, neuroscience, linguistics, anthropology, computer science, sociology and biology....
 and computer science
Computer science

Computer science is the study of the theoretical foundations of information and computation, and of practical techniques for their implementation and application in computer systems....
.

Holographic associative memory
Holographic associative memory

Holographic Associative Memory is part of the family of analog, correlation-based, associative, stimulus-response memories, where information is mapped onto the phase orientation of complex numbers operating....
 is another type of pattern matching scheme where a target small patterns can be searched from a large set of learned patterns based on cognitive meta-weight.

Uses

Within medical science, pattern recognition is the basis for computer-aided diagnosis
Computer-aided diagnosis

Computer-assisted detection is a procedure in medical science that supports the doctors interpretations and findings. Imaging techniques in X-ray diagnostics yield a great deal of information, the radiologist has to analyze and evaluate comprehensively in a short time....
 (CAD) systems. CAD describes a procedure that supports the doctor's interpretations and findings.

Typical applications are automatic speech recognition
Speech recognition

Speech recognition converts spoken words to machine-readable input . The term "voice recognition" is sometimes incorrectly used to refer to speech recognition, when actually referring to speaker recognition, which attempts to identify the person speaking, as opposed to what is being said....
, classification of text into several categories
Document classification

Document classification/categorization is a problem in information science. The task is to assign an electronic document to one or more Categorization, based on its contents....
 (e.g. spam/non-spam email messages), the automatic recognition of handwritten postal codes
Handwriting recognition

Handwriting recognition is the ability of a computer to receive and interpret intelligible handwritten input from sources such as paper documents, photographs, touch-screens and other devices....
 on postal envelopes, or the automatic recognition of images
Facial recognition system

A facial recognition system is a computer application for automatically identifying or verifying a person from a digital image or a video frame from a video source....
 of human faces. The last two examples form the subtopic image analysis
Image analysis

Image analysis is the extraction of meaningful information from s; mainly from digital images by means of digital image processing techniques. Image analysis tasks can be as simple as reading barcoded tags or as sophisticated as facial recognition system....
 of pattern recognition that deals with digital images as input to pattern recognition systems.

See also

  • Compound term processing
    Compound term processing

    Compound term processing is the name that is used for a category of techniques in Information retrieval applications that performs matching on the basis of compound terms....
  • Computer-aided diagnosis
    Computer-aided diagnosis

    Computer-assisted detection is a procedure in medical science that supports the doctors interpretations and findings. Imaging techniques in X-ray diagnostics yield a great deal of information, the radiologist has to analyze and evaluate comprehensively in a short time....
  • Data mining
    Data mining

    Data mining is the process of extracting hidden patterns from data. As more data is gathered, with the amount of data doubling every three years, data mining is becoming an increasingly important tool to transform this data into information....
  • EURASIP Journal on Advances in Signal Processing
    EURASIP Journal on Advances in Signal Processing

    EURASIP Journal on Advances in Signal Processing is a Peer review, open access journal.It was previously known as the EURASIP Journal on Applied Signal Processing....
  • List of computer vision conferences
    List of computer vision conferences

    This is a list of the most prominent conferences within the field of Computer vision, Pattern recognition and to some extent ....
  • List of numerical analysis software
    List of numerical analysis software

    Listed here are a number of computer programs used for performing numerical analysis calculations:* ADMB is a software suite for non-linear statistical modeling based on C++ which uses automatic differentiation....
  • Predictive analytics
    Predictive analytics

    Predictive analytics encompasses a variety of techniques from statistics and data mining that analyze current and historical data to make predictions about future events....
  • Prior knowledge for pattern recognition
    Prior knowledge for pattern recognition

    Pattern recognition is a very active field of research intimately bound to machine learning. Also known as classification or statistical classification, pattern recognition aims at building a classifier that can determine the class of an input pattern....
  • Pareidolia
    Pareidolia

    The term pareidolia describes a psychological phenomenon involving a vague and random stimulation being perceived as significant. Common examples include seeing images of animals or faces in clouds, the man in the moon, and hearing hidden messages on records played in reverse....


Further reading

  • Keinosuke Fukunaga, (1990) Statistical Pattern Recognition, Morgan Kaufmann, ISBN 0-12-269851-7.
  • Christopher M. Bishop, (2006) Pattern Recognition and Machine Learning, Springer, ISBN 0-387-31073-8.
  • Sergios Theodoridis, Konstantinos Koutroumbas, (2009) Pattern Recognition (4th edition), Elsevier, ISBN 978-1-59749-272-0.
  • Phiroz Bhagat, (2005) Pattern Recognition in Industry Elsevier, ISBN 0-08-044538-1.
  • Richard O. Duda, Peter E. Hart
    Peter E. Hart

    Peter E. Hart is an American computer scientist and entrepreneur. He was chairman and president of Ricoh Innovations, Inc., which he founded in 1997....
    , David G. Stork (2001) Pattern classification (2nd edition), Wiley, New York, ISBN 0-471-05669-3.
  • Dietrich Paulus and Joachim Hornegger (1998) Applied Pattern Recognition (2nd edition), Vieweg. ISBN 3-528-15558-2
  • J. Schuermann: Pattern Classification: A Unified View of Statistical and Neural Approaches, Wiley&Sons, 1996, ISBN 0-471-13534-8
  • Sholom Weiss and Casimir Kulikowski (1991) Computer Systems That Learn, Morgan Kaufmann. ISBN 1-55860-065-5
  • MOHD SAIFULNIZAM and KRISHNA KUMAR (2008) Budget System, Morgan Kaufmann. ISBN 1-55860-065-5


External links

  • or
  • or
  • or
  • (Journal of the Pattern Recognition Society)
  • Neocognitron application (C#) to recognize patterns with how to videos are available: