Deep Learning-Based Plant Classification Using Nonaligned Thermal and Visible Light Images

Ganbayar Batchuluun, Se Hyun Nam and Kang Ryoung Park ()
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Ganbayar Batchuluun: Division of Electronics and Electrical Engineering, Dongguk University, 30 Pildong-ro, 1-gil, Jung-gu, Seoul 04620, Korea
Se Hyun Nam: Division of Electronics and Electrical Engineering, Dongguk University, 30 Pildong-ro, 1-gil, Jung-gu, Seoul 04620, Korea
Kang Ryoung Park: Division of Electronics and Electrical Engineering, Dongguk University, 30 Pildong-ro, 1-gil, Jung-gu, Seoul 04620, Korea

Mathematics, 2022, vol. 10, issue 21, 1-18

Abstract: There have been various studies conducted on plant images. Machine learning algorithms are usually used in visible light image-based studies, whereas, in thermal image-based studies, acquired thermal images tend to be analyzed with a naked eye visual examination. However, visible light cameras are sensitive to light, and cannot be used in environments with low illumination. Although thermal cameras are not susceptible to these drawbacks, they are sensitive to atmospheric temperature and humidity. Moreover, in previous thermal camera-based studies, time-consuming manual analyses were performed. Therefore, in this study, we conducted a novel study by simultaneously using thermal images and corresponding visible light images of plants to solve these problems. The proposed network extracted features from each thermal image and corresponding visible light image of plants through residual block-based branch networks, and combined the features to increase the accuracy of the multiclass classification. Additionally, a new database was built in this study by acquiring thermal images and corresponding visible light images of various plants.

Keywords: plant image; image classification; thermal image; visible light image; deep learning (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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