標題: DETECTION OF FUSARIUM WILT ON PHALAENOPSIS STEM BASE REGION USING BAND SELECTION TECHNIQUES
作者: Lee, Meng-Chueh
Ma, Kenneth-Yeonkong
Ouyang, Yen-Chieh
Mang Ou-Yang
Guo, Horng-Yuh
Liu, Tsang-Sen
Chen, Hsian-Min
Wu, Chao-Cheng
Chang, Chgein-I
電機工程學系
Department of Electrical and Computer Engineering
關鍵字: Hyperspectral image;Phalaenopsis;fusarium wilt;Band selection;OSP;CEM;SVM
公開日期: 1-一月-2018
摘要: Phalaenopsis is a significant agriculture product with high economic value in Taiwan. However, the fusarium wilt causes Phalaenopsis leaves turning yellow, thinning, water loss, and finally died. This paper presents an emerging method to detect fusarium wilt on Phalaenopsis stem base. In order to build the detection models, the hyperspectral databases are generated form two statues of Phalaenopsis samples, which are health and disease sample. We applied band selection (BS) processing base on band prioritization (BP) and band de-correlation (BD) to extract the significant bands and eliminate the redundant bands. Then, three algorithms were used, orthogonal subspace projection (OSP), constrain energy minimization (CEM), and support vector machine (SVM) to detect the fusarium wilt.
URI: http://hdl.handle.net/11536/150850
ISSN: 2153-6996
期刊: IGARSS 2018 - 2018 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM
起始頁: 2777
結束頁: 2780
顯示於類別:會議論文