Strawberry Plant Alive Status Detection and Relative Pixel Based Plant Localization

Abstract

Abstract Autonomous plant alive status monitoring and corresponding localization of individual plant are two important tasks in precision agriculture. In this study, two new methods that are crucial to such robotic operations are proposed. First, a low cost and light scene invariant approach is proposed to differentiate green and yellow leaves using distinct color-ratio index ranges. Second, based on the relative pixel information of neighboring plants, an extended Kalman filter is used to determine plant positions. Such a differential style localization method is shown to be capable of achieving a similar centimeter level accuracy as light detection and ranging (LIDAR) or real-time kinematic-global positioning system (RTK-GPS) based approaches, but with a much lower upfront and maintenance cost. These two new methods are successfully validated in a nearby commercial field.

Plant phenotyping relevance

植物の生存状態（緑葉・黄葉によるalive status）を画像から判定する新規手法を開発し、圃場で検証しているため、植物フェノタイピング手法が中心です。

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