Abstract A computer-implemented
system and method are provided for counting
orchard items, including winter buds, flower buds, flowers, fruitlets, and fruit, and estimating volume, weight, and / or yield from sampled video frames selected according to at least one of time, distance travelled,
location data, or motion-sensor data during row-wise
orchard scanning by a moving handheld or vehicle-mounted device.
Orchard items that are substantially stationary relative to
orchard structure are associated across frames using a scene-level, non-object-specific camera-induced inter-frame displacement representing expected pixel-space translation of stationary scene elements and configurable distance-based gated association with gate size determined from at least
frame rate, expected camera speed, orchard row geometry, or scene depth variation, while unique identifiers are retained through configurable missed sampled frames so that each item is counted once during a visible lifespan within a scanned orchard segment comprising a row, bay, or block. For
fruit weight estimation, multiple frames associated with a same
unique identifier and representing different views of the same fruit item are used to generate polygon masks and fitted ellipses,
observable minor axes from the fitted ellipses are aggregated to derive an image-observed minor-axis characterisation, corresponding major axes are determined from
population-derived characterising data obtained from laboratory measurements of representative fruit items rather than directly extracted as primary inputs from the fitted ellipses used in the method, and ellipsoidal or spheroidal volume estimates based on the image-observed minor-axis characterisation and the determined major axes are converted to weight and yield outputs. Spatial outputs such as count maps, density maps, weight maps, and yield forecasts may be generated. 20 26 20 31 24 27 A pr 2 02 6 2 0 2 6 2 0 3 1 2 4 2 7 2 0 2 6 A p r 2 0 2 6 2 0 3 1 2 4 2 7 2 0 2 6 A p r