Finally, an apple recognition algorithm with colour difference R − B (red minus blue) and G − R (green minus red) was developed for apple images after June drop, and two different colour models were used to segment ripening period apple images. Several image processing algorithms and fruit counting algorithms were used to analyse the apple images. after June drop and during ripening, on the preferred western side of the tree row with a variability of between 70 and 170 fruit per tree, under natural daylight conditions at Bonn, Germany. ‘Gala’ apple digital images were captured twice, i.e. New apple fruit recognition algorithms based on colour features are presented to estimate the number of fruits and develop models for early prediction of apple yield, in a multi-disciplinary approach linking computer science with agricultural engineering and horticulture as part of precision agriculture.
