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A novel hyperspectral line-scan imaging method for whole surfaces of round shaped agricultural products

机译:圆形农产品全曲面的新型高光谱线扫描成像方法

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摘要

The present study has developed a novel line-scan technique for hyperspectral imaging (HSI) of the whole surface of a round object. The developed system uniquely incorporates an external optical assembly of four mirrors to view a rotating round object from two opposite sides and project a combined two-view image onto the aperture of line-scan HSI camera. This allows imaging of the whole surface of the round object to detect defects located on any part of that surface. For obtaining the two side views that include the areas around the poles, the design of the optical path requires consideration of the distance from the inside mirrors to the outside mirrors, and the inclination angles of the outside mirrors. The optimum mirror distance of 171.6 mm and mirror angle of 13.24 was determined by sequential quadratic programming (SQP). The system was first calibrated using four wooden spheres of various sizes and was demonstrated for potential whole-surface imaging of round-shaped fruits by scanning 101 apples each marked with six simulated defects at known positions across the fruit surface. By using 3D reconstruction images, the system was able to accurately detect all six dots on 78% of the apples, but detected 5 dots (undercounted) and 7 dots (overcounted) on 4% and 18% of the apples, respectively. The image processing algorithm investigated in this study will be used to develop real-time multispectral systems for whole-surface quality evaluation of rounded objects in the agrofood sector. Published by Elsevier Ltd on behalf of IAgrE.
机译:本研究开发了一种用于圆形物体的整个表面的高光谱成像(HSI)的新型线扫描技术。开发系统唯一地结合了四个镜的外部光学组件,以从两个相对侧观察旋转圆对象,并将组合的双视图像投影到线扫描HSI相机的孔上。这允许圆形物体的整个表面成像以检测位于该表面的任何部分的缺陷。为了获得包括围绕磁极周围的区域的两个侧视图,光路的设计需要考虑与内部镜的距离到外镜,以及外侧镜的倾斜角度。通过顺序二次编程(SQP)确定171.6mm的最佳镜像和13.24的镜子角度。首先使用各种尺寸的四个木球校准该系统,并通过扫描101苹果来证明圆形水果的潜在整体表面成像,每个苹果标有六个模拟缺陷在果实表面上的已知位置。通过使用3D重建图像,系统能够在78%的苹果上准确地检测所有六个点,但分别检测到5点(欠压)和7个点(超过18%的苹果。本研究中调查的图像处理算法将用于开发用于在农业食品部门中的圆形物体的全表面质量评估进行实时多光谱系统。 elsevier有限公司代表IAGRE出版。

著录项

  • 来源
    《Biosystems Engineering》 |2019年第2019期|共10页
  • 作者单位

    Univ Maryland Dept Mech Engn 1000 Hilltop Circle Baltimore MD 21250 USA;

    Chungnam Natl Univ Coll Agr &

    Life Sci Dept Biosyst Machinery Engn 99 Daehak Ro Daejeon 34134 South Korea;

    Univ Guelph Coll Engn &

    Phys Sci Intelligent Control &

    Estimat Lab 50 Stone Rd East Guelph ON N1G 2W1 Canada;

    Univ Maryland Dept Mech Engn 1000 Hilltop Circle Baltimore MD 21250 USA;

    USDA ARS Environm Microbial &

    Food Safety Lab Henry A Wallace Beltsville Agr Res Ctr Beltsville MD 20705 USA;

    Rural Dev Adm Natl Inst Agr Sci 310 Nonsaengmyeong Ro Jeonju Si 54875 Jeollabuk Do South Korea;

    USDA ARS Environm Microbial &

    Food Safety Lab Henry A Wallace Beltsville Agr Res Ctr Beltsville MD 20705 USA;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 农业生物学;农业工程;
  • 关键词

    Apples; Whole surface inspection; Line-scan; 3D reconstruction;

    机译:苹果;整个表面检查;线扫描;3D重建;
  • 入库时间 2022-08-19 22:59:28

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