• DocumentCode
    2233371
  • Title

    Study on Fruit Quality Inspection Based on Its Surface Color in Produce Logistics

  • Author

    Wang, Yizhong ; Cui, Yanhua ; Huang, George Q. ; Zhang, Ping ; Chen, Shaohui

  • Author_Institution
    Sch. of Electron. Inf. & Autom., Tianjin Univ. of Sci. & Technol., Tianjin, China
  • fYear
    2010
  • fDate
    13-15 Dec. 2010
  • Firstpage
    107
  • Lastpage
    111
  • Abstract
    A novel non-invasive and nondestructive fruit quality inspection method for produce logistics is proposed in this paper based on fruits´ surface color. In this method, an image of fruits is firstly taken, which is in the RGB color model. The image is then transferred from the RGB color model to the HSI color model, and is segmented based on hue value to separate the fruits and its background. After that, the simplified histograms of hue H and saturation S of fruits´ surface color are calculated, which are used as the input of a designed back propagation (BP) network. The output of the BP network is the quality description of the inspected fruits. After training, the quality of fruits is inspected by the BP network according to the simplified histograms of H and S of fruits´ surface color. Experiments are conducted for the quality inspection of bananas with satisfied results, which show the feasibility and reliability of the proposed quick fruit quality inspection method.
  • Keywords
    backpropagation; food products; inspection; neural nets; nondestructive testing; production engineering computing; quality management; HSI color model; RGB color model; backpropagation network; hue; inspected fruits; nondestructive fruit quality inspection logistics; noninvasive fruit quality inspection; quality description; quick fruit quality inspection; saturation; simplified histograms; surface color; color; fruit; image processing; produce logistics; quality inspection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Manufacturing Automation (ICMA), 2010 International Conference on
  • Conference_Location
    Hong Kong
  • Print_ISBN
    978-1-4244-9018-9
  • Electronic_ISBN
    978-0-7695-4293-5
  • Type

    conf

  • DOI
    10.1109/ICMA.2010.47
  • Filename
    5695164