Last edited by Jumi
Friday, July 17, 2020 | History

4 edition of Optical pattern recognition with microlasers found in the catalog.

Optical pattern recognition with microlasers

Optical pattern recognition with microlasers

  • 70 Want to read
  • 30 Currently reading

Published by U.S. Dept. of Commerce, Technology Administration, National Institute of Standards and Technology in Gaithersburg, MD .
Written in English

    Subjects:
  • Optical pattern recognition -- Technological innovations

  • Edition Notes

    StatementEung Gi Paek
    SeriesNISTIR -- 6017
    ContributionsNational Institute of Standards and Technology (U.S.)
    The Physical Object
    FormatMicroform
    Pagination23, [17] p.
    Number of Pages23
    ID Numbers
    Open LibraryOL13623029M
    OCLC/WorldCa39135972

      Both methods employ ANN for pattern recognition in conjunction with features extraction approaches and digital signal processing. In the first method, asynchronous amplitude sampling is the features extraction method. For high-speed optical communications, new approach using ANN trained by the features of linear optical sampling is implemented. SPIE books provide content relating to optics and photonics, such as Selected Papers on Semiconductor Quantum Dots, edited by Frank W. Wise. Selected Papers on Optical Pattern Recognition Using Joint Transform Correlation. Mohammad S. Alam. Member: $ Non-member: $ Selected Papers on Optical Pattern Recognition.

    Statistical Pattern Recognition, 3 rd Edition: Provides a self-contained introduction to statistical pattern recognition. Includes new material presenting the analysis of complex networks. Introduces readers to methods for Bayesian density estimation. Presents descriptions of new applications in biometrics, security, finance and condition. Abstract: This article addresses the development of and recent advances in the rapidly growing field of optical pattern recognition. In optical pattern recognition there are two basic approaches; namely, matched filtering and associative memories. The first employs optical correlator architectures and the latter uses optical neural networks (NNs).

      Pattern matching consists of the ability to identify the class of input signals or patterns. Pattern matching ANN are typically trained using supervised learning techniques. One application where artificial neural nets have been applied extensively is optical character recognition (OCR).   Optical Character Recognition and Office The files I converted (ie, opened with Office Word) were PDFs from a scanned image of an out-of-print book I am republishing. They were image files and it did a very good job performing OCR on them. Where it could not "read" it placed an image (this was mostly of smudges from the original.


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Optical pattern recognition with microlasers Download PDF EPUB FB2

This book provides a comprehensive review of optical pattern recognition, covering theoretical aspects as well as details of practical implementations and signal processing techniques.

The first chapter is devoted to pattern recognition performed with optical correlators. Later chapters discuss new approaches based on neural networks, wavelet transforms, and the fractional Fourier transform.5/5(1).

This book provides a comprehensive review of optical pattern recognition, covering theoretical aspects as well as details of practical implementations and signal processing approaches based on neural networks, wavelet transforms, and the fractional Fourier transform are discussed, as are optical-electronic hybrid systems.4/5(1).

This book provides a comprehensive review of optical pattern recognition, covering theoretical aspects as well as details of practical implementations and signal processing approaches based on neural networks, wavelet transforms, and the fractional Fourier transform are discussed, as Optical pattern recognition with microlasers book optical-electronic hybrid by:   Applications of photrefractive devices in optical pattern recognition Ziangyang Yang; Optical pattern recognition with microlasers Eung-Gi Paek; Optical properties and applications of bacteriorhodopsin Q.

Wang Song and Yu-He Zhang; Liquid-crystal spatial light modulators Aris Tanone and Suganda Jutamulia; Cited by: This study provides a basic understanding of the fundamentals of optical pattern recognition systems. An emphasis on the capabilities and limitations of such systems is presented.

This chapter discusses optical pattern recognition. Optical pattern recognition is a technique that is based upon the use of a video camera and a computer with the ability to store images. A CCD (charge coupled device) camera is often employed because it is more stable and dimensionally constant than a tube-based camera.

POLYMERS that exhibit the photorefractive effect—a light-induced modulation of refractive index—are emerging as attractive materials for optical devices and processing systems1,2. Here we.

An attractive concept in this field is reservoir computing which is based on coupled non-linear elements to enable for instance ultra-fast pattern recognition. We focus on the development of microlasers in a dense regular array for the implementation of photonic reservoir computing based on. Real-Time Optical Information Processing covers the most recent developments in optical information processing, pattern recognition, neural computing, and materials for devices in optical computing.

Intended for researchers and graduate students in signal and information processing with some elementary background in optics, the book provides both theoretical and practical information on the.

Optical character recognition (OCR) is the most prominent and successful example of pattern recognition to date. There are thousands of research papers and dozens of OCR products.

Optical Character Rcognition: An Illustrated Guide to the Frontier offers a perspective on the performance of current OCR systems by illustrating and explaining actual OCR errors. This book delivers a course module for advanced undergraduates, postgraduates and researchers of electronics, computing science, medical imaging, or wherever the study of identification and classification of objects by electronics-driven image processing and pattern recognition is relevant.

Pattern recognition is the automated recognition of patterns and regularities in has applications in statistical data analysis, signal processing, image analysis, information retrieval, bioinformatics, data compression, computer graphics and machine n recognition has its origins in statistics and engineering; some modern approaches to pattern recognition include the use.

Get this from a library. Optical pattern recognition with microlasers. [Eung Gi Paek; National Institute of Standards and Technology (U.S.)]. Buy Pattern Recognition and Machine Learning (Information Science and Statistics) (Information Science and Statistics) Newer (Colored) by Christopher M.

Bishop (ISBN: ) from Amazon's Book Store. Everyday low prices and free delivery on eligible orders. His research interests include optical information processing, image encryption, watermarking, digital holography, interferometry, correlation based optical pattern recognition, and fractional Fourier transform-based signal processing.

He is a senior member of OSA, SPIE and life fellow of Optical. 19 Microcomputer-based programmable optical correlator for automatic pattern recognition and identification Francis T.S. Yu, Jacques E. Ludman (Optics Letters ) 22 Adaptive real-time pattern recognition using a liquid crystal TV based joint transform correlator Francis T.S.

Yu, Suganda Jutamulia, Tsongneng W. Lin, Don A. Gregory (Applied. in interferometry, such as in electronic speckle pattern interferometry (ESPI) [ 26 ]. Metrology of deformations and vibrations is a major application area of digital holography [ 27 ].

Optical processing, such as pattern recognition and encryption, by digital holography also offers new capabilities [ 28 ]. This much-needed text brings the treatment of optical pattern recognition up-to-date in one comprehensive resource.

Optical pattern recognition, one of the first implementations of Fourier Optics, is now widely used, and this text provides an accessible introduction for readers who wish to get to grips with how holography is applied in a practical context.

In this paper we evaluate Optical Character Recognition (OCR) of 19th century Fraktur scripts without book-specific training using mixed models, i.e.

models trained to recognize a variety of fonts and typesets from previously unseen sources. We describe the training process leading to strong mixed OCR models and compare them to freely available models of the popular open source engines.

The book will no doubt be of value to students and practitioners."-Sargur N. Srihari, SUNY Distinguished Professor, Department of Computer Science and Engineering, and Director, Center of Excellence for Document Analysis and Recognition (CEDAR), University at Buffalo, The State University of New York "The disciplines of optical character.

The design, analysis and use of correlation pattern recognition algorithms requires background information, including linear systems theory, random variables and processes, matrix/vector methods, detection and estimation theory, digital signal processing and optical processing.

This book provides a needed review of this diverse background.Book Review: Optical pattern recognition using holographic techniques. (Electronic Systems Engineering Series). By Neil Collings, Addison- Wesley Publishing Company, pp. ISBN Price: £17Pattern Recognition of the SCImago Journal Rank of (e.g.

Pattern Recognition sincePattern Recognition Letters since ). Conferences named ‘Optical Pattern Recognition’, ‘Automatic Target Recognition’, and ‘Signal Processing, Sensor Fusion, and Target Recognition’—all of them organized by the International Society on.