Hyperspectral Imaging System with Rotation Platform for Investigation of Jujube Skin Defects

A novel object rotation hyperspectral imaging system with the wavelength range of 468–950 nm for investigating round-shaped fruits was developed. This system was used to obtain the reflection spectra of jujubes for the application of surface defect detection. Compared to the traditional linear scan...

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Main Authors: Quoc Thien Pham, Nai-Shang Liou
Format: Article
Language:English
Published: MDPI AG 2020-04-01
Series:Applied Sciences
Subjects:
Online Access:https://www.mdpi.com/2076-3417/10/8/2851
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spelling doaj-cee29c4645794b34bd1fbb98b68f53392020-11-25T02:29:51ZengMDPI AGApplied Sciences2076-34172020-04-01102851285110.3390/app10082851Hyperspectral Imaging System with Rotation Platform for Investigation of Jujube Skin DefectsQuoc Thien Pham0Nai-Shang Liou1Department of Mechanical Engineering, Southern Taiwan University of Science and Technology, Tainan 710, TaiwanDepartment of Mechanical Engineering, Southern Taiwan University of Science and Technology, Tainan 710, TaiwanA novel object rotation hyperspectral imaging system with the wavelength range of 468–950 nm for investigating round-shaped fruits was developed. This system was used to obtain the reflection spectra of jujubes for the application of surface defect detection. Compared to the traditional linear scan system, which can scan about 49% of jujube surface in one scan pass, this novel object rotation scan system can scan 95% of jujube surface in one scan pass. Six types of jujube skin condition, including rusty spots, decay, white fungus, black fungus, cracks, and glare, were classified by using hyperspectral data. Support vector machine (SVM) and artificial neural network (ANN) models were used to differentiate the six jujube skin conditions. Classification effectiveness of models was evaluated based on confusion matrices. The percentage of classification accuracy of SVM and ANN models were 97.3% and 97.4%, respectively. The object rotation scan method developed for this study could be used for other round-shaped fruits and integrated into online hyperspectral investigation systems.https://www.mdpi.com/2076-3417/10/8/2851hyperspectral imagingrotation scanpostharvest processsingjujube skinsurface defect detection
collection DOAJ
language English
format Article
sources DOAJ
author Quoc Thien Pham
Nai-Shang Liou
spellingShingle Quoc Thien Pham
Nai-Shang Liou
Hyperspectral Imaging System with Rotation Platform for Investigation of Jujube Skin Defects
Applied Sciences
hyperspectral imaging
rotation scan
postharvest processsing
jujube skin
surface defect detection
author_facet Quoc Thien Pham
Nai-Shang Liou
author_sort Quoc Thien Pham
title Hyperspectral Imaging System with Rotation Platform for Investigation of Jujube Skin Defects
title_short Hyperspectral Imaging System with Rotation Platform for Investigation of Jujube Skin Defects
title_full Hyperspectral Imaging System with Rotation Platform for Investigation of Jujube Skin Defects
title_fullStr Hyperspectral Imaging System with Rotation Platform for Investigation of Jujube Skin Defects
title_full_unstemmed Hyperspectral Imaging System with Rotation Platform for Investigation of Jujube Skin Defects
title_sort hyperspectral imaging system with rotation platform for investigation of jujube skin defects
publisher MDPI AG
series Applied Sciences
issn 2076-3417
publishDate 2020-04-01
description A novel object rotation hyperspectral imaging system with the wavelength range of 468–950 nm for investigating round-shaped fruits was developed. This system was used to obtain the reflection spectra of jujubes for the application of surface defect detection. Compared to the traditional linear scan system, which can scan about 49% of jujube surface in one scan pass, this novel object rotation scan system can scan 95% of jujube surface in one scan pass. Six types of jujube skin condition, including rusty spots, decay, white fungus, black fungus, cracks, and glare, were classified by using hyperspectral data. Support vector machine (SVM) and artificial neural network (ANN) models were used to differentiate the six jujube skin conditions. Classification effectiveness of models was evaluated based on confusion matrices. The percentage of classification accuracy of SVM and ANN models were 97.3% and 97.4%, respectively. The object rotation scan method developed for this study could be used for other round-shaped fruits and integrated into online hyperspectral investigation systems.
topic hyperspectral imaging
rotation scan
postharvest processsing
jujube skin
surface defect detection
url https://www.mdpi.com/2076-3417/10/8/2851
work_keys_str_mv AT quocthienpham hyperspectralimagingsystemwithrotationplatformforinvestigationofjujubeskindefects
AT naishangliou hyperspectralimagingsystemwithrotationplatformforinvestigationofjujubeskindefects
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