Automated Vine Row Detection Algorithm

VIC, Agriculture - Pinpoint plant stress for precision treatment

Digital Falcon has developed a new method to automatically segment crops with distinct row and canopy configurations (e.g. vineyard, fruit orchards and vegetable crops) in aerial imagery. The algorithm uses skeletonisation techniques, developed for fingerprint analysis, to detect the crop’s unique signature and seperate canopy pixels from non-canopy pixels. When evaluated on a commercial vineyard, the algorithm achieved a vine row detection accuracy of 97.1%. By simplify the skill set required to collect and analyse remotely sensed data, we can start to realise the potential UAS in precision agriculture and environmental monitoring.

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Digital Falcon

Digital Falcon

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