Leaf Temperature Measurement Using Low-Resolution Thermal Camera Based on Thresholding and Clustering Techniques

Abstract

Leaf temperature can indicate photosynthetic rates, leaf water status, and stomata conductance. Leaf temperature can be measured using thermal resistance sensors, thermocouple devices, infrared thermometers, or infrared thermal imaging devices. Additionally, measuring leaf temperature using a thermal camera is simple and efficient. Therefore, the research proposes a leaf temperature measurement method using AMG8833, a low-resolution (64 pixels) thermal camera. The proposed system adopts an image segmentation technique to extract the leaf area from a thermal image. The leaf temperature is then calculated by averaging the temperature values on the leaf area. The proposed system aims to utilize a low-cost and low-resolution thermal camera for measuring the leaf temperature. The proposed approach is evaluated using real images of the Dieffenbachia plant, a popular ornamental plant that can be easily planted. In the experiments, fourteen segmentation methods consisting of eight thresholding techniques and six clustering techniques are evaluated. The experimental findings on the Dieffenbachia plant indicate that the most accurate leaf temperature measurements are obtained using local thresholding with an absolute error of 0.0109 and k-means clustering with an absolute error of 0.0134. The proposed method provides a simple, effective, and low-cost leaf temperature measurement system compared to the existing systems which employ high-cost commercial thermal cameras and complex measurement methods.