Application of digital image processing to the measurement of Leaf Area Index (LAI) of rice plants (Oryza Sativa L.)

Indonesia's main staple food, rice, is by far the largest commodity. In improving food security through the productivity of this local staple crop, care is needed from planting to harvesting. One of the physiological parameters that can determine biomass production and photosynthesis in rice is the leaf. We can measure this part of the plant through various methods ranging from conventional techniques to computer image processing techniques such as canny edge detection and ImageJ software. Through the comparison of these two methods, it is found that canny edge detection has a smaller average error value when compared to ImageJ, which is 3.76% and 4.53% respectively. With this final value, it is proven that canny edge detection can be an alternative technique to measure the value of LAI (Leaf Area Index) in rice plants. Keywords: Canny, ImageJ, Image Processing, Leaf Width, Rice