MISC

2008年9月

FEATURES EXTRACTION FOR EGGPLANT FRUIT GRADING SYSTEM USING MACHINE VISION

APPLIED ENGINEERING IN AGRICULTURE
  • V. K. Chong
  • ,
  • N. Kondo
  • ,
  • K. Ninomiya
  • ,
  • T. Nishi
  • ,
  • M. Monta
  • ,
  • K. Namba
  • ,
  • Q. Zhang

24
5
開始ページ
675
終了ページ
684
記述言語
英語
掲載種別
出版者・発行元
AMER SOC AGRICULTURAL & BIOLOGICAL ENGINEERS

Machine vision based grading for agricultural crops has been well developed and accepted as an attractive grading method. However, machine vision based grading for eggplant fruit is not available yet. This study reports oil the attempt to develop an eggplant grading machine using six CCD cameras as the sensing device. Feature extraction algorithms were developed to extract eggplant's features, i.e., length, diameter, volume, curvature, color homogeneity, calyx color, calyx area, and surface defect. The system could acquire six images per fruits covering the entire surface of the eggplant fruits. All agreement rate Of 78.0% was achieved in the feasibility study where the machine vision based grading was compared with manual grading. The throughput of the developed system was 0.3 second per fruit. Details of the system, an outline of the algorithm, and performance results are reported in this article.

Web of Science ® 被引用回数 : 14

リンク情報
Web of Science
https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000261073200017&DestApp=WOS_CPL

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