Fusarium Wilt Inspection for Phalaenopsis Using Uniform Interval Hyperspectral Band Selection Techniques

Bo Han Chen; Yen Chieh Ouyang; Mang Ou-Yang; Horng Yuh Guo; Tsang Sen Liu; Hsian Min Chen; Chao Cheng Wu; Chia Hsien Wen; Chgein I. Chang; Min Shao Shih

doi:10.1109/IGARSS39084.2020.9324496

Fusarium Wilt Inspection for Phalaenopsis Using Uniform Interval Hyperspectral Band Selection Techniques

Bo Han Chen, Yen Chieh Ouyang, Mang Ou-Yang, Horng Yuh Guo, Tsang Sen Liu, Hsian Min Chen, Chao Cheng Wu, Chia Hsien Wen, Chgein I. Chang, Min Shao Shih

Department of Electrical and Computer Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Scopus citations

Abstract

In this paper, we propose a method to inspect the quality of Phalaenopsis by using hyperspectral imaging techniques. Phalaenopsis is easy to get infected with Fusarium wilt. We use the k-means clustering method to find out that the reflection spectrum of Phalaenopsis stem changes. The methods of the Spectral Angle Mapper (SAM) and Constrained Energy Minimization (CEM) are then used to find the area of the infected area. The Harsanyi, Farrand and Chang (HFC) methods and virtual dimensions (VD) are used to estimate the amount of spectrum required for band selection (BS). Band priority (BP) is used to calculate the priority of each band, and band de-correlation (BD) will remove band data with high correlation with each other. Then use the support vector machine (SVM) to detect Phalaenopsis wilt. The detection accuracy of VNIR and SWIR is 0.81 and 0.86, respectively, with band selection.

Original language	English
Title of host publication	2020 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2020 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	2831-2834
Number of pages	4
ISBN (Electronic)	9781728163741
DOIs	https://doi.org/10.1109/IGARSS39084.2020.9324496
State	Published - 26 Sep 2020
Event	2020 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2020 - Virtual, Waikoloa, United States Duration: 26 Sep 2020 → 2 Oct 2020

Publication series

Name	International Geoscience and Remote Sensing Symposium (IGARSS)

Conference

Conference	2020 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2020
Country/Territory	United States
City	Virtual, Waikoloa
Period	26/09/20 → 2/10/20

Keywords

Band de-correlation
Band prioritization
Band selection
Constrain energy minimization
Spectral angle mapper
Spectral information divergence
Support vector machine
Virtual dimensionality

Access to Document

10.1109/IGARSS39084.2020.9324496

Cite this

Chen, B. H., Ouyang, Y. C., Ou-Yang, M., Guo, H. Y., Liu, T. S., Chen, H. M., Wu, C. C., Wen, C. H., Chang, C. I., & Shih, M. S. (2020). Fusarium Wilt Inspection for Phalaenopsis Using Uniform Interval Hyperspectral Band Selection Techniques. In 2020 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2020 - Proceedings (pp. 2831-2834). Article 9324496 (International Geoscience and Remote Sensing Symposium (IGARSS)). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IGARSS39084.2020.9324496

Chen, Bo Han ; Ouyang, Yen Chieh ; Ou-Yang, Mang et al. / Fusarium Wilt Inspection for Phalaenopsis Using Uniform Interval Hyperspectral Band Selection Techniques. 2020 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2020 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2020. pp. 2831-2834 (International Geoscience and Remote Sensing Symposium (IGARSS)).

@inproceedings{5127cd09a19b40559663c8b02f8dc001,

title = "Fusarium Wilt Inspection for Phalaenopsis Using Uniform Interval Hyperspectral Band Selection Techniques",

abstract = "In this paper, we propose a method to inspect the quality of Phalaenopsis by using hyperspectral imaging techniques. Phalaenopsis is easy to get infected with Fusarium wilt. We use the k-means clustering method to find out that the reflection spectrum of Phalaenopsis stem changes. The methods of the Spectral Angle Mapper (SAM) and Constrained Energy Minimization (CEM) are then used to find the area of the infected area. The Harsanyi, Farrand and Chang (HFC) methods and virtual dimensions (VD) are used to estimate the amount of spectrum required for band selection (BS). Band priority (BP) is used to calculate the priority of each band, and band de-correlation (BD) will remove band data with high correlation with each other. Then use the support vector machine (SVM) to detect Phalaenopsis wilt. The detection accuracy of VNIR and SWIR is 0.81 and 0.86, respectively, with band selection.",

keywords = "Band de-correlation, Band prioritization, Band selection, Constrain energy minimization, Spectral angle mapper, Spectral information divergence, Support vector machine, Virtual dimensionality",

author = "Chen, {Bo Han} and Ouyang, {Yen Chieh} and Mang Ou-Yang and Guo, {Horng Yuh} and Liu, {Tsang Sen} and Chen, {Hsian Min} and Wu, {Chao Cheng} and Wen, {Chia Hsien} and Chang, {Chgein I.} and Shih, {Min Shao}",

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year = "2020",

month = sep,

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doi = "10.1109/IGARSS39084.2020.9324496",

language = "English",

series = "International Geoscience and Remote Sensing Symposium (IGARSS)",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "2831--2834",

booktitle = "2020 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2020 - Proceedings",

address = "美國",

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Chen, BH, Ouyang, YC, Ou-Yang, M, Guo, HY, Liu, TS, Chen, HM, Wu, CC, Wen, CH, Chang, CI & Shih, MS 2020, Fusarium Wilt Inspection for Phalaenopsis Using Uniform Interval Hyperspectral Band Selection Techniques. in 2020 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2020 - Proceedings., 9324496, International Geoscience and Remote Sensing Symposium (IGARSS), Institute of Electrical and Electronics Engineers Inc., pp. 2831-2834, 2020 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2020, Virtual, Waikoloa, United States, 26/09/20. https://doi.org/10.1109/IGARSS39084.2020.9324496

Fusarium Wilt Inspection for Phalaenopsis Using Uniform Interval Hyperspectral Band Selection Techniques. / Chen, Bo Han; Ouyang, Yen Chieh; Ou-Yang, Mang et al.
2020 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2020 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2020. p. 2831-2834 9324496 (International Geoscience and Remote Sensing Symposium (IGARSS)).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Fusarium Wilt Inspection for Phalaenopsis Using Uniform Interval Hyperspectral Band Selection Techniques

AU - Chen, Bo Han

AU - Ouyang, Yen Chieh

AU - Ou-Yang, Mang

AU - Guo, Horng Yuh

AU - Liu, Tsang Sen

AU - Chen, Hsian Min

AU - Wu, Chao Cheng

AU - Wen, Chia Hsien

AU - Chang, Chgein I.

AU - Shih, Min Shao

PY - 2020/9/26

Y1 - 2020/9/26

N2 - In this paper, we propose a method to inspect the quality of Phalaenopsis by using hyperspectral imaging techniques. Phalaenopsis is easy to get infected with Fusarium wilt. We use the k-means clustering method to find out that the reflection spectrum of Phalaenopsis stem changes. The methods of the Spectral Angle Mapper (SAM) and Constrained Energy Minimization (CEM) are then used to find the area of the infected area. The Harsanyi, Farrand and Chang (HFC) methods and virtual dimensions (VD) are used to estimate the amount of spectrum required for band selection (BS). Band priority (BP) is used to calculate the priority of each band, and band de-correlation (BD) will remove band data with high correlation with each other. Then use the support vector machine (SVM) to detect Phalaenopsis wilt. The detection accuracy of VNIR and SWIR is 0.81 and 0.86, respectively, with band selection.

AB - In this paper, we propose a method to inspect the quality of Phalaenopsis by using hyperspectral imaging techniques. Phalaenopsis is easy to get infected with Fusarium wilt. We use the k-means clustering method to find out that the reflection spectrum of Phalaenopsis stem changes. The methods of the Spectral Angle Mapper (SAM) and Constrained Energy Minimization (CEM) are then used to find the area of the infected area. The Harsanyi, Farrand and Chang (HFC) methods and virtual dimensions (VD) are used to estimate the amount of spectrum required for band selection (BS). Band priority (BP) is used to calculate the priority of each band, and band de-correlation (BD) will remove band data with high correlation with each other. Then use the support vector machine (SVM) to detect Phalaenopsis wilt. The detection accuracy of VNIR and SWIR is 0.81 and 0.86, respectively, with band selection.

KW - Band de-correlation

KW - Band prioritization

KW - Band selection

KW - Constrain energy minimization

KW - Spectral angle mapper

KW - Spectral information divergence

KW - Support vector machine

KW - Virtual dimensionality

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U2 - 10.1109/IGARSS39084.2020.9324496

DO - 10.1109/IGARSS39084.2020.9324496

M3 - Conference contribution

AN - SCOPUS:85101996342

T3 - International Geoscience and Remote Sensing Symposium (IGARSS)

SP - 2831

EP - 2834

BT - 2020 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2020 - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2020 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2020

Y2 - 26 September 2020 through 2 October 2020

ER -

Chen BH, Ouyang YC, Ou-Yang M, Guo HY, Liu TS, Chen HM et al. Fusarium Wilt Inspection for Phalaenopsis Using Uniform Interval Hyperspectral Band Selection Techniques. In 2020 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2020 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2020. p. 2831-2834. 9324496. (International Geoscience and Remote Sensing Symposium (IGARSS)). doi: 10.1109/IGARSS39084.2020.9324496

Fusarium Wilt Inspection for Phalaenopsis Using Uniform Interval Hyperspectral Band Selection Techniques

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