Automated 3D Surface Reconstruction and Analysis of apple Near-Infrared data for the application of apple stem-end/calyx identification

Bin Zhu, Lu Jiang, Yang Tao

Research output: Contribution to conferencePaper

Abstract

Machine vision technologies have received more and more attention for automated apple sorting and grading applications. Currently most machine vision techniques used in apple automated processing are 2-D or 2.5-D based approaches, which usually have difficulties to identify apple stemend/calyx from defects. On the other hand, as one of the persistent problems, apple stem-end/calyx identification must be solved not only for the accurate defect inspection, but for efficient firmness measurement purposes. To solve above problem, a novel 3-D based apple near-infrared (NIR) data analysis strategy was proposed so that the apple stem-end/calyx could be identified, and hence differentiated from defect and normal tissue according to their different 3D shapes. Two automated 3-D data processing approaches were developed in this research: 1). 3-D quadratic facet model fitting, which employed a small concaved 3-D patch to fit 3-D apple surface, and the best fit could be found around stemend/calyx area; and 2). 3-D shape enhanced transform (SET), which enhanced the apple stemend/calyx area, and made it easily detectable, according to the 3D surface gradient difference between the stem-end/calyx and the apple surface. Apple 3-D surface was reconstructed from 2-D NIR images according to Shape-From-Shading (SFS) method. Unlike 2.5-D approach, the SFS took advantage of the whole image information, which meant a more detailed apple 3D description could be obtained. The proposed 3-D approaches didn't depend on the location of the stem-end/calyx on the apple surface, making it more suitable for apples orientated randomly. There was also no additional light source required in the imaging system: normal visible white light plus a NIR filter was enough. In addition, the proposed 3-D approaches were found to be robust to the noise and incomplete image data. Finally, the experiment results demonstrated the effectiveness of proposed 3-D approaches, and an overall detection rate above 90% was achieved.

Original languageEnglish (US)
StatePublished - Nov 7 2007
Event2007 ASABE Annual International Meeting, Technical Papers - Minneapolis, MN, United States
Duration: Jun 17 2007Jun 20 2007

Other

Other2007 ASABE Annual International Meeting, Technical Papers
CountryUnited States
CityMinneapolis, MN
Period6/17/076/20/07

Keywords

  • 3D reconstruction
  • 3D shape enhanced transform (SET)
  • Apple stem-end/calyx identification
  • Automated detection
  • Facet model
  • NIR imaging
  • Shape-from-shading (SFS)

ASJC Scopus subject areas

  • Agricultural and Biological Sciences(all)
  • Engineering(all)

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  • Cite this

    Zhu, B., Jiang, L., & Tao, Y. (2007). Automated 3D Surface Reconstruction and Analysis of apple Near-Infrared data for the application of apple stem-end/calyx identification. Paper presented at 2007 ASABE Annual International Meeting, Technical Papers, Minneapolis, MN, United States.