Please use this identifier to cite or link to this item:
http://repository.kln.ac.lk/handle/123456789/18382
Title: | Identification of Water Stress of Plants Using Image Processing. |
Authors: | De Silva, R. Senanayake, P. A. |
Keywords: | Image Processing Leaf Water Stress Recognition LWC RGB Decomposition |
Issue Date: | 2017 |
Publisher: | 8th International Conference on Business & Information ICBI – 2017, Faculty of Commerce and Management Studies, University of Kelaniya, Sri Lanka. |
Citation: | De Silva, R., and Senanayake, P. A. (2017). Identification of Water Stress of Plants Using Image Processing. 8th International Conference on Business & Information ICBI – 2017, Faculty of Commerce and Management Studies, University of Kelaniya, Sri Lanka. p.37. |
Abstract: | Low Leaf Water Content (LWC) levels in plants lead to water stress, and the leaves become wilted. Most farmers use slight wilting as the visual indicator to water their plants. Though the researchers have studied LWC of plants extensively using remote sensing and complex methods, the agricultural industry cannot use them as they are complex and costly. This paper presents a simple method of recognizing water stress of leaves using leaf images taken by a smartphone. Our initial experiment on a large sample of mung bean leaves indicates that RGB values of images are related to water stress. The method would be beneficial to the agricultural industry as once further developed; it could be used to determine the watering time point of plants. The process can be automated by capturing the images by a camera mounted on a land or an aerial robot and processing them online. |
URI: | http://repository.kln.ac.lk/handle/123456789/18382 |
Appears in Collections: | ICBI 2017 |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.