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Sartenejas, June 28th, 2009. **1.3. ** Fingerprint: Definition, types and Characteristics. ** The Pattern Recognition is a basic attribute in the animal behavior. Also it is possible to define it as the science that is busy with the processes on engineering, computation and mathematics related to physical objects and/or abstract objects, with the intention of extracting information that allows to establish properties of or between sets of the above mentioned objects.
 * Written by María Alejandra Fernández M. **
 * PATTERN RECOGNITION AND FINGERPRINT RECOGNITION **
 * CONTENT **
 * 1. **** Introduction **
 * 1.1. **  Pattern Recognition's Definition.
 * 1.2. **  Applications of Pattern Recognition.
 * 2. **** The Aim: **    To identify and to compare fingerprints across Pattern Recognition Methods.
 * 3. **** The Development: **    To give response to our aim, that is to say, to explain how it is possible to identify and to compare fingerprints with Pattern Recognition Methods.
 * 4. **** Conclusion
 * INTRODUCTION **

The stages of the Process of Pattern Recognition are: - Physical System (Reality). - Modeling by the not mathematical specialist. - Systems of Measurement. - Data obtained. - Validation of the data. - Definition of the model of Recognition who more is convenient to continue. - Mathematical Modeling. - Selection of variables. - Design of the classifier. - Test and validation of the classifier. - Application of the model. - Interpretation of results. - Feedback.

A system of complete Pattern Recognition consists of a sensor that gathers the observations to classify, a system of extraction of characteristics that transforms the information observed in numerical or symbolic values, and a system of classification or description that, based on the extracted characteristics, classifies the measurement.

The classification uses habitually one of the following procedures: statistical classification (or theory of the decision), Syntactic classification (or structural). The pattern statistical recognition is based on the statistical characteristics of the pattern, assuming that it has been generated by a probability system. The pattern structural recognition is based on the structural relations of the characteristics.

For the classification it is possible to use a set of learning, of which already the classification of the information is known "a priori" and is used to train to the system, being theresultant strategy known as "supervised learning". The learning can be "not supervised" also, the system does not have a set to learn to classify the information "a priori", but it is based on statistical calculations to classify the pattern.

Methods of pattern recognition are useful in many applications such as information retrieval, data mining, document image analysis and recognition, computational linguistics, forensics, biometrics and bioinformatics.

The object of interest for this Written Project is the application of pattern recognition techniques in fingerprint recognition.

“Fingerprint identification is one of the most well-known and publicized biometrics. Because of its uniqueness and consistency over time, fingerprints have been used for identification for over a century, more recently becoming automated (i.e. a biometric) due to advancements in computing capabilities. Fingerprint identification is popular because of the inherent ease in acquisition, the numerous sources (ten fingers) available for collection, and their established use and collections by law enforcement and immigration”. [|www.**biometric**coe.gov/Modalities/**Fingerprint**.htm]” THE FINGERPRINT:

“A smoothly flowing pattern formed by alternating crests (ridges) and troughs (valleys) on the palmer aspect of hand is called a palmprint. Formation of a palmprint depends on the initial conditions of the embryonic mesoderm from which they develop. The pattern on pulp of each terminal phalanx is considered as an individual pattern and is commonly referred to as a fingerprint. A fingerprint is believed to be unique to each person (and each finger). Fingerprints of even identical twins are different”. Handbook of image and video processing written by Alan Conrad Bovik.

Also, the fingerprint can be defined as the brand that leaves the yolk of the finger in an object on having touched it. Because of it, it is possible to obtain fingerprints purposely, on to having impregnated to the finger with a coloring matter. Common types of Fingerprints: The patterns of Fingerprints are divided in three big groups that consist of: Arches, Curves and Spirals. Approximately 5% of all the fingerprints are Arches, 30% are Spirals and 65% are curved.



In fingerprint recognition, the algorithms of recognition, commonly, are basing on the detection of the "minutiae", the "ridges" that they form, and the relationship between them.

Image taken from: http://perso.wanadoo.fr/fingerchip/index.htm

References:

Wikipedia: § Richard O. Duda, Peter E. Hart, David G. Stork (2001)  // Pattern classification // (2ª edición), Wiley, New York,  [|ISBN 0471056693]. § Dietrich Paulus and Joachim Hornegger (1998)  // Applied Pattern Recognition // (2ª edición), Vieweg. [|ISBN 3-528-15558-2] § J. Schuermann:  // Pattern Classification: A Unified View of Statistical and Neural Approaches //, Wiley&Sons, 1996,  [|ISBN 0471135348] § Sholom Weiss and Casimir Kulikowski (1991)  // Computer Systems That Learn //, Morgan Kaufmann. [|ISBN 1-55860-065-5] Others Websites:
 * [| http://www2.uca.es/dept/leng_sist_informaticos/preal/23041/transpas/B-IntroalRecdePatrones/ppframe.htm]
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