Journal of Biosystems Engineering

  • 제39권3호
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  • Pages.166-173
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  • 2014
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  • 1738-1266(pISSN)
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  • 2234-1862(eISSN)
한국농업기계학회 (Korean Society for Agricultural Machinery)
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Multispectral Wavelength Selection to Detect 'Fuji' Apple Surface Defects with Pixel-sampling Analysis

  • Park, Soo Hyun (Department of Biosystems & Biomaterials Science and Engineering, Seoul National University) ;
  • Lee, Hoyoung (Environmental Microbiology and Food Safety Laboratory, Animal and Natural Resources Institute, Agricultural Research Service, U.S. Department of Agriculture) ;
  • Noh, Sang Ha (Department of Biosystems & Biomaterials Science and Engineering, Seoul National University)
  • 투고 : 2014.06.18
  • 심사 : 2014.08.20
  • 발행 : 2014.09.01
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초록

Purpose: In this study, we focused on the image processing method to determine the external quality of Fuji apples by identifying surface defects such as scabs and bruises. Method: A CCD camera was used to capture filter images with 24 different wavelengths ranging between 530 nm and 1050 nm. Image subtraction and division operations were performed to distinguish the defect area from the normal areas including calyx, stem, and glaring on the apple surface image. All threshold values of the image were examined to reveal the defect area of pretreated filter images. Results: The developed operation methods were [image (720 nm) - image (900 nm)]/image (700 nm) for bruise detection and [image (740 nm) - image (900 nm)]/image (590 nm) for scab detection, which revealed 81% and 90% recognition ratios, respectively. Conclusions: Our results showed several optimal wavelengths and image processing methods to detect Fuji apple surface defects such as bruises and scabs.

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참고문헌

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피인용 문헌

  1. Image Processing Methods for Measurement of Lettuce Fresh Weight vol.40, pp.1, 2015, https://doi.org/10.5307/JBE.2015.40.1.089