Assessment of External Properties for Identifying Banana Fruit Maturity Stages Using Optical Imaging Techniques Article Swipe
Jiajun Zhuang
,
Chaojun Hou
,
Yu Tang
,
Yong He
,
Qiwei Guo
,
Aimin Miao
,
Zhenyu Zhong
,
Shaoming Luo
·
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.3390/s19132910
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.3390/s19132910
The maturity stage of bananas has a considerable influence on the fruit postharvest quality and the shelf life. In this study, an optical imaging based method was formulated to assess the importance of different external properties on the identification of four successive banana maturity stages. External optical properties, including the peel color and the local textural and local shape information, were extracted from the stalk, middle and tip of the bananas. Specifically, the peel color attributes were calculated from individual channels in the hue-saturation-value (HSV), the International Commission on Illumination (CIE) L*a*b* and the CIE L*ch color spaces; the textural information was encoded using a local binary pattern with uniform patterns (UP-LBP); and the local shape features were described by histogram of oriented gradients (HOG). Three classifiers based on the naïve Bayes (NB), linear discriminant analysis (LDA) and support vector machine (SVM) algorithms were adopted to evaluate the performance of identifying banana fruit maturity stages using the different optical appearance features. The experimental results demonstrate that overall identification accuracies of 99.2%, 100% and 99.2% were achieved using color appearance features with the NB, LDA and SVM classifiers, respectively; overall accuracies of 92.6%, 86.8% and 93.4% were obtained using local textural features for the three classifiers, respectively; and overall accuracies of only 84.3%, 83.5% and 82.6% were obtained using local shape features with the three classifiers, respectively. Compared to the complicated calculation of both the local textural and local shape properties, the simplicity and high accuracy of the peel color property make it more appropriate for identifying banana fruit maturity stages using optical imaging techniques.
Related Topics
Concepts
Artificial intelligence
Local binary patterns
Pattern recognition (psychology)
Histogram
Support vector machine
Linear discriminant analysis
Mathematics
Histogram of oriented gradients
Hue
Naive Bayes classifier
Postharvest
Local color
Color space
Computer science
Horticulture
Biology
Image (mathematics)
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/s19132910
- https://www.mdpi.com/1424-8220/19/13/2910/pdf?version=1561962911
- OA Status
- gold
- Cited By
- 32
- References
- 38
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2953672223
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W2953672223Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/s19132910Digital Object Identifier
- Title
-
Assessment of External Properties for Identifying Banana Fruit Maturity Stages Using Optical Imaging TechniquesWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2019Year of publication
- Publication date
-
2019-07-01Full publication date if available
- Authors
-
Jiajun Zhuang, Chaojun Hou, Yu Tang, Yong He, Qiwei Guo, Aimin Miao, Zhenyu Zhong, Shaoming LuoList of authors in order
- Landing page
-
https://doi.org/10.3390/s19132910Publisher landing page
- PDF URL
-
https://www.mdpi.com/1424-8220/19/13/2910/pdf?version=1561962911Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
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https://www.mdpi.com/1424-8220/19/13/2910/pdf?version=1561962911Direct OA link when available
- Concepts
-
Artificial intelligence, Local binary patterns, Pattern recognition (psychology), Histogram, Support vector machine, Linear discriminant analysis, Mathematics, Histogram of oriented gradients, Hue, Naive Bayes classifier, Postharvest, Local color, Color space, Computer science, Horticulture, Biology, Image (mathematics)Top concepts (fields/topics) attached by OpenAlex
- Cited by
-
32Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 4, 2024: 6, 2023: 7, 2022: 6, 2021: 4Per-year citation counts (last 5 years)
- References (count)
-
38Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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