Weed detection by analysis of multispectral images acquired under uncontrolled illumination conditions

A. Amziane; O. Losson; B. Mathon; L. Macaire; A. Duménil

doi:10.1117/12.2586823

16 July 2021 Weed detection by analysis of multispectral images acquired under uncontrolled illumination conditions

A. Amziane, O. Losson, B. Mathon, L. Macaire, A. Duménil

Proceedings Volume 11794, Fifteenth International Conference on Quality Control by Artificial Vision; 1179414 (2021) https://doi.org/10.1117/12.2586823
Event: Fifteenth International Conference on Quality Control by Artificial Vision, 2021, Tokushima, Japan

Abstract

Localized weed control is one of the promising solutions to improve the application of herbicides in crop fields. To target weeds exclusively during the spray, their location in the field must be accurately determined. As weeds have colorimetric properties similar to crops, their detection may be difficult especially under varying illumination conditions. Among available technologies, multispectral cameras provide radiance images with a high spectral resolution allowing for the analysis of vegetation signatures beyond the visible and near infrared domains. In this study, we address the problem of outdoor weed detection and identification using multispectral and RGB-NIR imaging.

Citation Download Citation

A. Amziane, O. Losson, B. Mathon, L. Macaire, and A. Duménil "Weed detection by analysis of multispectral images acquired under uncontrolled illumination conditions", Proc. SPIE 11794, Fifteenth International Conference on Quality Control by Artificial Vision, 1179414 (16 July 2021); https://doi.org/10.1117/12.2586823

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