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Introduction

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Pattern Recognition

Part of the book series: Undergraduate Topics in Computer Science ((UTICS,volume 0))

Abstract

Pattern recognition can be defined as the classification of data based on knowledge already gained or on statistical information extracted from patterns and/or their representations.

It has several important applications. Multimedia document recognition (MDR) and automatic medical diagnosis are two such applications. For example, in MDR we have to deal with a combination of text, audio and video data. The text data may be made up of alpha-numerical characters corresponding to one or more natural languages. The audio data could be in the form of speech or music. Similarly, the video data could be a single image or a sequence of images—for example, the face of a criminal, his fingerprint and signature could come in the form of a single image. It is also possible to have a sequence of images of the same individual moving in an airport in the form of a video clip.

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Bibliography

  1. Bishop, C. M. Neural Networks for Pattern Recognition. New Delhi: Oxford University Press. 2003.

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Correspondence to M. Narasimha Murty .

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© 2011 Universities Press (India) Pvt. Ltd.

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Murty, M.N., Devi, V.S. (2011). Introduction. In: Pattern Recognition. Undergraduate Topics in Computer Science, vol 0. Springer, London. https://doi.org/10.1007/978-0-85729-495-1_1

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  • DOI: https://doi.org/10.1007/978-0-85729-495-1_1

  • Publisher Name: Springer, London

  • Print ISBN: 978-0-85729-494-4

  • Online ISBN: 978-0-85729-495-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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