Using Image Processing for Plant Health Monitoring
Abstract
The problem farmers face in knowing the health status of the plants during the growth period has
limited the yield produced, informed application of pesticide and sustainable agriculture. The
challenge to better plant health monitoring is traceable to the methods used in the monitoring
process.
The aim of this project was to investigate the application of image processing in solving plant
health monitoring problems. The specific objectives that the project sought to address include;
identification of spectral features for plant health state classification, developing of a model for
plant health classification, developing image processing segmentations based on the models for
plant health classification and developing a prototype for the plant health monitoring system. The
intention was to have the data collected easily, understood, and interpreted for early mitigation
plans on the onset of a change of plant health status.
In this project, two approaches were used where an unmanned aerial vehicle platform was used for
carrying cameras to capture aerial images on specific coordinates. The images were then processed
through an algorithm that was developed to identify Normalized Difference Vegetation Index
(NDVI) data to generate the required data for development of the plant health monitoring prototype
system. This was a continuous monitoring system as the plants were monitored through the
planting to harvesting.
The plant health monitoring system prototype using image processing was developed. The
acquired aerial images were processed from the planting to harvesting and a graph produced for
tracking the health status of the plants.
The testing and evaluation findings revealed that a variation in graph pattern would indicate the
onset of a change in health status. The evaluation of the system showed that the system can improve
plant health monitoring for farmers as well as provide effective ways in determining plant health
status.
Publisher
University of Nairobi
Rights
Attribution-NonCommercial-NoDerivs 3.0 United StatesUsage Rights
http://creativecommons.org/licenses/by-nc-nd/3.0/us/Collections
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