Challenges and solutions of optical-based nondestructive quality inspection for robotic fruit and vegetable grading systems: A technical review. (November 2018)
- Record Type:
- Journal Article
- Title:
- Challenges and solutions of optical-based nondestructive quality inspection for robotic fruit and vegetable grading systems: A technical review. (November 2018)
- Main Title:
- Challenges and solutions of optical-based nondestructive quality inspection for robotic fruit and vegetable grading systems: A technical review
- Authors:
- Zhang, Baohua
Gu, Baoxing
Tian, Guangzhao
Zhou, Jun
Huang, Jichao
Xiong, Yingjun - Abstract:
- Abstract: Background: Optical techniques, including computer vision, spectral imaging, near-infrared technology and other emerging imaging and spectroscopy techniques, have been rapidly developing and widely applied in fruit and vegetable grading systems for nondestructive quality inspecting and grading over the past decades. However, automatic detection of quality and grading is still difficult due to some still existing challenges, which are the key of blocking their commercialization in robotic fruit and vegetable grading systems. The challenges include the following aspects: the influence of physical and biological variability, whole surface detection, discrimination between defects and stems/calyxes, unobvious defect detection, robustness of the features and algorithms, as well as rapid optical detection system development. These challenges can reduce the fruit or vegetable quality inspection accuracy, thus greatly reducing automatic level of the quality inspecting and grading machines. Scope and approach: As agricultural engineers with about eight years of technical experience in fruit grading systems, we believe the ultimate goal of each scientific research should seek its task in serving the engineering. So, we have made many attempts to solve the challenges and increase the automation of the grading machines. Key findings and conclusions: The review gives a detailed summary about the challenges and solutions of optical-based nondestructive quality inspection forAbstract: Background: Optical techniques, including computer vision, spectral imaging, near-infrared technology and other emerging imaging and spectroscopy techniques, have been rapidly developing and widely applied in fruit and vegetable grading systems for nondestructive quality inspecting and grading over the past decades. However, automatic detection of quality and grading is still difficult due to some still existing challenges, which are the key of blocking their commercialization in robotic fruit and vegetable grading systems. The challenges include the following aspects: the influence of physical and biological variability, whole surface detection, discrimination between defects and stems/calyxes, unobvious defect detection, robustness of the features and algorithms, as well as rapid optical detection system development. These challenges can reduce the fruit or vegetable quality inspection accuracy, thus greatly reducing automatic level of the quality inspecting and grading machines. Scope and approach: As agricultural engineers with about eight years of technical experience in fruit grading systems, we believe the ultimate goal of each scientific research should seek its task in serving the engineering. So, we have made many attempts to solve the challenges and increase the automation of the grading machines. Key findings and conclusions: The review gives a detailed summary about the challenges and solutions of optical-based nondestructive quality inspection for fruit or vegetable grading systems from the perspective of engineering. Particular attention has been paid to the techniques that can improve the automation degree of the grading robot in this review. The advantages and disadvantages of the solutions are compared and discussed. Additionally, the remaining engineering challenges and future trends are also discussed. Highlights: A technical review from the perspective of engineer are presented. The challenges that influence automatic sorting are described. The available solutions are summarized in detail. The potential future trends are also reported. … (more)
- Is Part Of:
- Trends in food science & technology. Volume 81(2018)
- Journal:
- Trends in food science & technology
- Issue:
- Volume 81(2018)
- Issue Display:
- Volume 81, Issue 2018 (2018)
- Year:
- 2018
- Volume:
- 81
- Issue:
- 2018
- Issue Sort Value:
- 2018-0081-2018-0000
- Page Start:
- 213
- Page End:
- 231
- Publication Date:
- 2018-11
- Subjects:
- Imaging techniques -- Computer vision -- Hyperspectral imaging -- Multispectral imaging -- Spectroscopy techniques -- Nondestructive quality inspection -- Robotic fruit grading system
Food industry and trade -- Periodicals
Food -- Biotechnology -- Periodicals
664.005 - Journal URLs:
- http://www.sciencedirect.com/science/journal/09242244 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.tifs.2018.09.018 ↗
- Languages:
- English
- ISSNs:
- 0924-2244
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 9049.593000
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
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