Plants, like other living things, have biological clocks that allow them to respond the changes in time and environment1). At day, plants do photosynthesis to produce carbohydrate such as sugar. While at night, plants distribute the stored the carbohydrate to grow leaves, stem flowers, fruits, and roots. Analysis of plant growth and motion at night might be used as an indicator of plant response due to environmental change and conditions.The objective of this study was to develop an automatic plant motion analysis with machine vision applying optical flow technique. The night photos were captured with each 30 min. interval by using an infrared camera (Pi NoIR) installed in the Raspberry Pi B+, running the Raspbian Whezzy 3.18 and infrared LED light. This capturing device was located at 1 m above the plant. The plant motions were analyzed by using the optical flow method in the OpenCV libraries. The experiment was conducted in a tomato (Solanum lycopersicum) house at the Kyushu University. Optical flow is one of the motion detection methods to analyze the motion between two consecutive images. Assuming an object pixel at time t, the same intensity part was found from the image at a time after the motion. Differentiating the constraint gives the following equation, where are the motion vector and the time derivative. The distance and direction of motion will be used as the indicator for plant diagnosis in relation with environmental data.
Oral presentation at The Joint Conference on Environmental Engineering in Agriculture 2015. Iwate University, Morioka, Japan.