Citrus surface defect identification based on PCS-2D-Otsu and CGWO-DT-SVM
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Media Technology,Software
Link
https://link.springer.com/content/pdf/10.1007/s11042-023-17341-2.pdf
Reference31 articles.
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2. Blasco J, Aleixos N, Gómez J et al (2007) Citrus sorting by identification of the most common defects using multispectral computer vision[J]. J Food Eng 83(3):384–393. https://doi.org/10.1016/j.jfoodeng.2007.03.027
3. Cubero S, Lee WS, Aleixos N et al (2016) Automated systems based on machine vision for inspecting citrus fruits from the field to postharvest—a review[J]. Food Bioprocess Technol 9(10):1623–1639. https://doi.org/10.1007/s11947-016-1767-1
4. Li J, Rao X, Wang F et al (2013) Automatic detection of common surface defects on oranges using combined lighting transform and image ratio methods[J]. Postharvest Biol Technol 82:59–69. https://doi.org/10.1016/j.postharvbio.2013.02.016
5. Khoje SA, Bodhe SK, Adsul A (2013) Automated skin defect identification system for fruit grading based on discrete curvelet transform[J]. Int J Eng Technol 5(4):3251–3256. https://doi.org/10.1016/j.postharvbio.2013.02.016
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