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Radon and Projection Transform-Based Computer Vision

Algorithms, A Pipeline Architecture, and Industrial Applications

  • Textbook
  • © 1988

Overview

Authors:
  1. Jorge L. C. Sanz

    1. Computer Science Department, IBM Almaden Research Center, San Jose, USA

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  2. Eric B. Hinkle

    1. Computer Science Department, IBM Almaden Research Center, San Jose, USA

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  3. Anil K. Jain

    1. Electrical and Computer Engineering Department, University of California at Davis, Davis, USA

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Part of the book series: Springer Series in Information Sciences (SSINF, volume 16)

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Table of contents (9 chapters)

  1. Front Matter

    Pages I-VIII
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  2. Introduction

    • Jorge J. C. Sanz, Eric B. Hinkle, Anil K. Jain
    Pages 1-14

  3. Model and Computation of Digital Projections

    • Jorge J. C. Sanz, Eric B. Hinkle, Anil K. Jain
    Pages 15-26

  4. Architectures

    • Jorge J. C. Sanz, Eric B. Hinkle, Anil K. Jain
    Pages 27-36

  5. Projections Along General Contours

    • Jorge J. C. Sanz, Eric B. Hinkle, Anil K. Jain
    Pages 37-41

  6. P3E-Based Image Analysis Algorithms and Techniques

    • Jorge J. C. Sanz, Eric B. Hinkle, Anil K. Jain
    Pages 43-70

  7. P3E-Based Image Processing Algorithms and Techniques

    • Jorge J. C. Sanz, Eric B. Hinkle, Anil K. Jain
    Pages 71-85

  8. Radon Transform Theory for Random Fields and Optimum Image Reconstruction from Noisy Projections

    • Jorge J. C. Sanz, Eric B. Hinkle, Anil K. Jain
    Pages 87-93

  9. Machine Vision Techniques for Visual Inspection

    • Jorge J. C. Sanz, Eric B. Hinkle, Anil K. Jain
    Pages 95-104

  10. Conclusion

    • Jorge J. C. Sanz, Eric B. Hinkle, Anil K. Jain
    Pages 105-105

  11. Back Matter

    Pages 107-123
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Keywords

About this book

This book deals with novel machine vision architecture ideas that make real-time projection-based algorithms a reality. The design is founded on raster-mode processing, which is exploited in a powerful and flexible pipeline. We concern ourselves with several image analysis algorithms for computing: projections of gray-level images along linear patterns (i. e. , the Radon transform) and other curved contours; convex hull approximations; the Hough transform for line and curve detection; diameters; moments and principal components, etc. Addition­ ally, we deal with an extensive list of key image processing tasks, which involve generating: discrete approximations of the inverse Radon transform operator; computer tomography reconstructions; two-dimensional convolutions; rotations and translations; multi-color digital masks; the discrete Fourier transform in polar coordinates; autocorrelations, etc. Both the image analysis and image processing algorithms are supported by a similar architecture. We will also of some of the above algorithms to the solution of demonstrate the applicability various industrial visual inspection problems. The algorithms and architectural ideas surveyed here unleash the power of the Radon and other non-linear transformations for machine vision applications. We provide fast methods to transform images into projection space representa­ tions and to backtrace projection-space information into the image domain. The novelty of this approach is that the above algorithms are suitable for implementa­ tion in a pipeline architecture. Specifically, random access memory and other dedicated hardware components which are necessary for implementation of clas­ sical techniques are not needed for our algorithms.

Authors and Affiliations

  • Computer Science Department, IBM Almaden Research Center, San Jose, USA

    Jorge L. C. Sanz, Eric B. Hinkle

  • Electrical and Computer Engineering Department, University of California at Davis, Davis, USA

    Anil K. Jain

Bibliographic Information

  • Book Title: Radon and Projection Transform-Based Computer Vision

  • Book Subtitle: Algorithms, A Pipeline Architecture, and Industrial Applications

  • Authors: Jorge L. C. Sanz, Eric B. Hinkle, Anil K. Jain

  • Series Title: Springer Series in Information Sciences

  • DOI: https://doi.org/10.1007/978-3-642-73012-2

  • Publisher: Springer Berlin, Heidelberg

  • eBook Packages: Springer Book Archive

  • Copyright Information: Springer-Verlag Berlin Heidelberg 1988

  • Softcover ISBN: 978-3-642-73014-6Published: 10 December 2011

  • eBook ISBN: 978-3-642-73012-2Published: 07 March 2013

  • Series ISSN: 0720-678X

  • Edition Number: 1

  • Number of Pages: VIII, 123

  • Topics: Algorithm Analysis and Problem Complexity

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