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Optical pattern recognition IV

13-14 April 1993, Orlando, Florida
  • 536 Pages
  • 1.15 MB
  • 3396 Downloads
  • English

SPIE , Bellingham, Wash., USA
Optical pattern recognition -- Congr
Other titlesOptical pattern recognition 4., Optical pattern recognition four.
StatementDavid P. Casasent, chair/editor ; sponsored and published by SPIE--the International Society for Optical Engineering.
GenreCongresses.
SeriesProceedings / SPIE--the International Society for Optical Engineering -- v. 1959., Proceedings of SPIE--the International Society for Optical Engineering -- v. 1959.
ContributionsCasasent, David Paul., Society of Photo-optical Instrumentation Engineers.
The Physical Object
Paginationxi, 536 p. :
ID Numbers
Open LibraryOL19567609M
ISBN 100819411957
ISBN 139780819411952
LC Control Number93084043
OCLC/WorldCa29263239

Get this from a library. Optical pattern recognition IV: AprilOrlando, Florida. [D P Casasent; Society of Photo-optical Instrumentation Engineers.; SPIE Digital Library.;]. 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 Optical pattern recognition IV book, wavelet transforms, and the fractional Fourier transform.5/5(1).

Optical Character Recognition: An Illustrated Guide to the Frontier will pique the interest of users and developers of OCR products and desktop scanners, as well as teachers and students of pattern recognition, artificial intelligence, and information retrieval.

The first chapter compares the character recognition abilities of humans and by:   The era of detailed comparisons of the merits of techniques of pattern recognition and artificial intelligence and of the integration of such techniques into flexible and powerful systems has confirm the editors of this fourth volume of Pattern Recognition in Practice, in their preface to the 42 quality papers are sourced from a broad range of international specialists.

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

Description Optical pattern recognition IV FB2

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.

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. Optical Signal Processing is a collection of synopses of the works of many experts in the different fields of optical signal processing.

The book also includes systems or algorithms that have been successfully tried and used. while Part II covers topics related to pattern recognition such as optical feature extraction and unconventional. 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 Optical pattern recognition IV book background in optics, the book provides both theoretical and practical information on the.

Emerging Trends in Image Processing, Computer Vision and Pattern Recognition. Book • In order to obtain a high success rate of OCR (optical character recognition) performed on text images, the main target of filters is, however, to reduce the noise around characters in the image.

Thereby, I created two new nonlinear efficient image. 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. Pattern Recognition. Book • Third Edition • It also focuses on Optical character recognition (OCR) systems that are commercially available.

An OCR system has a “front end” device consisting of a light source, a scan lens, a document transport, and a detector. Clustering Algorithms IV. 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 by:   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.

Download Optical pattern recognition IV FB2

Optical Character Recognition: An Illustrated Guide to the Frontier will pique the interest of users and developers of OCR products and desktop scanners, as well as teachers and students of pattern recognition, artificial intelligence, and information retrieval.

The first chapter compares the character recognition abilities of humans and computers. Selected Papers on Optical Pattern Recognition (SPIE Milestone Series Vol. MS) by Francis T. Yu (Author, Editor), Shizhuo Yin (Author, Editor) ISBN ISBN Why is ISBN important.

ISBN. This bar-code number lets you verify that you're getting exactly the right version or edition of a book. This book presents novel and advanced topics in Medical Image Processing and Computational Vision in order to solidify knowledge in the related fields and define their key stakeholders.

It contains extended versions of selected papers presented in VipIMAGE – IV International ECCOMAS Thematic. Optical pattern recognition of letters by a joint-transform correlator using a ferroelectric liquid-crystal spatial light modulator Tadao Iwaki, Yasuyuki Mitsuoka (Optics Letters ) Feature-extracted joint transform correlation Mohammad S.

Alam (Applied Optics ). Optical Pattern Recognition by Francis T. Yu,available at Book Depository with free delivery worldwide. drag-&-drop to stack or merge ˚les, or use the embedded OCR (Optical Character Recognition) feature to convert them to a searchable e to convert them to a searchable PDF.

Hardware Requirements Pentium IV GHz processor (Pentium IV GHz processor recommended) CD-ROM Driver One available USB Port (USB recommended). This book covers most of the image processing steps that can be used to build an OCR system. It is a good refence if someone is new to OCR or is doing an OCR and is looking to improve the s: 2.

Get this from a library. Optical and digital pattern recognition: JanuaryLos Angeles, California. [Hua-Kuang Liu; Paul S Schenker; Society of Photo-optical Instrumentation Engineers.; IEEE Computer Society.; Pattern Recognition Society.;]. 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. Contributors; Preface; 1. Pattern recognition with optics Francis T. Yu and Don A.

Details Optical pattern recognition IV FB2

Gregory; 2. Hybrid neural networks for nonlinear pattern recognition Taiwei Lu; 3. Wavelets, optics, and pattern recognition Yao Li and Yunglong Sheng; 4. Applications of the fractional Fourier transform to optical pattern recognition David Mendlovic, Zeev Zalesky and Haldum M. Oxaktas; 5. Optical character recognition is a classic example of the application of a pattern classifier, see OCR-example.

The method of signing one's name was captured with stylus and overlay starting in The strokes, speed, relative min, relative max, acceleration and. Optical character recognition or optical character reader (OCR) is the electronic or mechanical conversion of images of typed, handwritten or printed text into machine-encoded text, whether from a scanned document, a photo of a document, a scene-photo (for example the text on signs and billboards in a landscape photo) or from subtitle text superimposed on an image (for example: from a.

Joint transform correlator performing pure phase correlation for optical pattern recognition. Journal of Modern Optics: Vol. 43, No. 10, pp. The Linked Data Service provides access to commonly found standards and vocabularies promulgated by the Library of Congress.

This includes data values and the controlled vocabularies that house them. Datasets available include LCSH, BIBFRAME, LC Name Authorities, LC Classification, MARC codes, PREMIS vocabularies, ISO language codes, and more.

Optical character recognition, usually abbreviated to OCR, is the mechanical or electronic conversion of scanned or photographed images of typewritten or printed text into machine-encoded/computer.

These include invariant pattern recognition, image normalization, image registration, focus/ defocus measurement, and watermarking. This book presents a survey of both recent and traditional image analysis and pattern recognition methods, based on image moments, and offers new concepts of invariants to linear filtering and implicit s: 1.

We systematically compare and analyze a set of key components in unsupervised optical flow to identify which photometric loss, occlusion handling, and smoothness regularization is most effective. Alongside this investigation we construct a number of novel improvements to unsupervised flow models, such as cost volume normalization, stopping the gradient at the occlusion mask, encouraging.Print book: EnglishView all editions and formats: Rating: (not yet rated) 0 with reviews - Be the first.

Subjects: Optical pattern recognition. Electronic data processing. More like this: Similar Items.embedded OCR (Optical Character Recognition) feature to convert them to a searchable e to convert them to a searchable PDF. Headquarters: [email protected] Hardware Requirements Pentium IV GHz processor (Pentium IV GHz processor recommended) CD-ROM Driver One available USB Port (USB recommended) 1GB RAM or higher recommended.