Automatic Leaf Motion Analysis Using Optical Flow To Diagnose Plant Behavior In Response To Environmental Changes

Abstract: We have proposed an automatic leaf motion analysis based on Infrared (IR) photography. The proposed system allows continuous, high-resolution time-lapse imaging, independent of the present of visible light, and based on open source platform. The utilization of microcomputer as a capturing unit might increase the simplicity and flexibility. The IR camera positioned above the plant as top view projection to capture the foliage images. As the motion tracking, the Optical Flow method was adopted, implementing the Lucas-Kanade technique with Shi-Tomasi corner detection. Optical flow is one of the motion detection methods to analyze the motion between two consecutive images by differentiating the constraint. Displacement distance and direction angle were used as a parameter for evaluation with regards to circadian rhythm. As the result, the proposed automatic leaf motion analysis could perform a continuous IR time-lapse photography and analyze the lateral 2D motion using the Optical Flow method. The highest probability of displacement distance observed at 6px (48%) and the direction angle was at 180° (39.2%). According to the visual appearance of time series data, the motion displacement seems to have a regular pattern resembles the circadian rhythm with regards to environmental changes although the noise also appears. To verify the relation between displacement distance, motion angle and circadian rhythm, analysis of phase and amplitude of data using a Fast Fourier Transform Nonlinear Least Squares (FFT-NLS) method will be in our future works.

Key Words: Plant motion, optical flow, leaf motion, circadian rhythm, motion analysis

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