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Introduction

  • Jorge J. C. Sanz
  • Eric B. Hinkle
  • Anil K. Jain
Part of the Springer Series in Information Sciences book series (SSINF, volume 16)

Abstract

A frequently expressed view in image analysis is that a general purpose vision system must be capable of generating rich descriptions without knowledge of specific objects in a scene. Defining the capabilities of such systems has received considerable research attention in the past several years. It is recognized that issues of system engineering play an essential role in the successful development of large computer vision systems. Moreover, it has been observed that computational issues such as architectural limitations, file structures, etc., have to some extent impeded progress in other areas of computer vision [Redd78]. Pragmatic aspects of computer vision have been extensively discussed in connection to basic image analysis capabilities such as edge detection, shape representation, segmentation, etc. [Erma78, Etch83, Neva78]

Keywords

Machine Vision Pipeline Architecture Image Processing Problem Automate Visual Inspection Machine Vision Application 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1988

Authors and Affiliations

  • Jorge J. C. Sanz
    • 1
  • Eric B. Hinkle
    • 1
  • Anil K. Jain
    • 2
  1. 1.Computer Science DepartmentIBM Almaden Research CenterSan JoseUSA
  2. 2.Electrical and Computer Engineering DepartmentUniversity of California at DavisDavisUSA

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