Lettuce growth prediction in plant factory using image processing technology

Image processing technology has been widely utilized in measuring growth levels of plants, controlling damage by harmful insects, and determining the proper harvesting time in plant factories, and proving the greater potential. This study aims to analyze and predict lettuce growth by monitoring growing lettuce from deep flow technique system and sprayed water culture system and processing the captured images. The plant factory has a total of eight beds, Consists of different light environments. The configuration of the experimental devices separated as imaging device to capture images and computer for image processing. The lettuce images were captured by means of a CCD camera, and then the background was separated from the lettuce by removing the independent pixels after the images were binarized using Microsoft Visual C++ 6.0. Growth of lettuce was analyzed through pixel of lettuce, and we compared with growing-related data. As a result, judged deemed possible to predict the growth of lettuce using image processing in a plant factory. Better quality of lettuce can be produced efficiently through prediction of growth.