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Please use this identifier to cite or link to this item: http://hdl.handle.net/11375/30156
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dc.contributor.authorBaek I-
dc.contributor.authorCho B-K-
dc.contributor.authorGadsden SA-
dc.contributor.authorEggleton C-
dc.contributor.authorOh M-
dc.contributor.authorMo C-
dc.contributor.authorKim MS-
dc.date.accessioned2024-09-08T17:37:49Z-
dc.date.available2024-09-08T17:37:49Z-
dc.date.issued2019-12-
dc.identifier.issn1537-5110-
dc.identifier.urihttp://hdl.handle.net/11375/30156-
dc.description.abstractThe 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 agro-food sector.-
dc.publisherElsevier-
dc.rights.uri7-
dc.subject4605 Data Management and Data Science-
dc.subject46 Information and Computing Sciences-
dc.subject40 Engineering-
dc.subject2 Zero Hunger-
dc.titleA novel hyperspectral line-scan imaging method for whole surfaces of round shaped agricultural products-
dc.typeArticle-
dc.date.updated2024-09-08T17:37:48Z-
dc.contributor.departmentMechanical Engineering-
dc.rights.licenseAttribution-NonCommercial-NoDerivs - CC BY-NC-ND-
dc.identifier.doihttps://doi.org/10.1016/j.biosystemseng.2019.09.014-
Appears in Collections:Mechanical Engineering Publications

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