@inproceedings{abac6f8536c440b593fa07c2a41726ab,
title = "Application of remote sensing for detecting plant disease using color and morphological features",
abstract = "Remote sensing provides the ability for relatively rapid and early detection of the spatial distribution of a plant disease using methods based on thermography and canopy reflectance in visual and near-infrared wavebands. By remote mapping using color imaging and subsequent data analysis routines, it is possible to realize early detection, identification, and quantification of different relevant plant diseases. In the present work, an applicability of remote sensing with digital color imaging for detecting plant disease is demonstrated. The color and morphological features are used for analysis and classification purposes. As a case study, the image processing is applied to the color photos of banana fields obtained by a manned aerial vehicle equipped with a high resolution camera. Major banana diseases (e.g. Panama etc.) exhibit symptoms on leaf area in their earlier stage of infection. Change of color and morphology features act as criteria used to identify and classify the disease. The results of plant disease recognition and identification are demonstrated.",
keywords = "Color features, Digital color imaging, Image segmentation, Panama wilt, Plant disease",
author = "Arkadi Zilberman and {Ben Asher}, Jiftah and Kopeika, {Natan S.} and Yaniv Reshef",
note = "Publisher Copyright: {\textcopyright} 2019 SPIE.; Remote Sensing for Agriculture, Ecosystems, and Hydrology XXI 2019 ; Conference date: 09-09-2019 Through 11-09-2019",
year = "2019",
month = jan,
day = "1",
doi = "10.1117/12.2532810",
language = "English",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Neale, {Christopher M. U.} and Antonino Maltese",
booktitle = "Remote Sensing for Agriculture, Ecosystems, and Hydrology XXI",
address = "United States",
}