Proceedings of the Korean Society for Agricultural Machinery Conference (한국농업기계학회:학술대회논문집)

Korean Society for Agricultural Machinery (한국농업기계학회)
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GRADING CUT ROSES BY COLOR IMAGE PROCESSING AND NEURAL NETWORK

  • Bae, Y.H. (Dept. of Agricultural Machinery Engineering, Sunchon National University) ;
  • Seo, H.S. (Agricultural R＆D Promotion Center)
  • Published : 2000.11.01
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Abstract

Sorting cut roses according to quality is very essential to increase the value of the product. Many factors are involved in determining the grade of cut roses: length, thickness, and straightness of stem, color and maturity of bud, and extra. Among these factors, the stem straightness and bud maturity are considered to be difficult to set proper classification criteria. In this study, a prototype machine and an analysis procedure were developed to grade cut roses according to stem straightness and bud maturity by utilizing color image processing and neural network. The test results indicated 15.8% classification error for stem straightness and 10.0% for bud maturity.

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