Automatic grape bunch detection in vineyards with an SVM classifier

Precise yield estimation in vineyards using image processing techniques has only been demonstrated conceptually on a small scale. Expanding this scale requires significant computational power where, by necessity, only small parts of the images of vines contain useful features. This paper introduces an image processing algorithm combining colour and texture information and the use of a support vector machine, to accelerate fruit detection by isolating and counting bunches in images. Experiments carried out on two varieties of red grapes (Shiraz and Cabernet Sauvignon) demonstrate an accuracy of 88.0% and recall of 91.6%. This method is also shown to remove the restriction on the field of view and background which plagued existing methods and is a first step towards precise and reliable yield estimation on a large scale.