• DocumentCode
    2700625
  • Title

    A machine vision extension for the Ruby programming language

  • Author

    Wedekind, J. ; Amavasai, B.P. ; Dutton, K. ; Boissenin, M.

  • Author_Institution
    Microsyst.&Machine Vision Lab., Sheffield Hallam Univ., Sheffield
  • fYear
    2008
  • fDate
    20-23 June 2008
  • Firstpage
    991
  • Lastpage
    996
  • Abstract
    Dynamically typed scripting languages have become popular in recent years. Although interpreted languages allow for substantial reduction of software development time, they are often rejected due to performance concerns. In this paper we present an extension for the programming language Ruby, called HornetsEye, which facilitates the development of real-time machine vision algorithms within Ruby. Apart from providing integration of crucial libraries for input and output, HornetsEye provides fast native implementations (compiled code) for a generic set of array operators. Different array operators were compared with equivalent implementations in C++. Not only was it possible to achieve comparable real-time performance, but also to exceed the efficiency of the C++ implementation in several cases. Implementations of several algorithms were given to demonstrate how the array operators can be used to create concise implementations.
  • Keywords
    C++ language; authoring languages; computer vision; specification languages; C++ language; HornetsEye; Ruby programming language; array operator; computer vision; image processing; machine vision extension; real-time machine vision algorithm; typed scripting language; Automation; Cameras; Computer languages; Hardware; Laboratories; Machine vision; Object recognition; Open source software; Signal processing algorithms; Software libraries; Computer Vision; Image Processing; Signal Processing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information and Automation, 2008. ICIA 2008. International Conference on
  • Conference_Location
    Changsha
  • Print_ISBN
    978-1-4244-2183-1
  • Electronic_ISBN
    978-1-4244-2184-8
  • Type

    conf

  • DOI
    10.1109/ICINFA.2008.4608143
  • Filename
    4608143