Detection of Grapes in Natural Environment Using Feedforward Neural Network as a Classifier - Doležel, Petr; Gago, Lumír; Škrabánek, Pavel (IEEE (Institute of Electrical and Electronics Engineers), 2016)
The recognition of wine grapes in images acquired in natural environment is a serious issue solved by researches dealing with precision viticulture. The detection of wine grapes of red kinds is a well managed problem. On the other hand, the detection of white grapes is still a challenging task. In this contribution, the classifier for white wine grapes recognition is introduced and evaluated. The classifier is based on an artificial neural network and is used in two ways which differ in image representation. Namely, the pixel intensities and histogram of oriented gradients are used for the representation of images. Then, feedforward multilayer neural network is applied as a classifier. The classifiers based on the histograms of oriented gradients seemed to be very effective - they were almost error free from the cross validation point of view and they performed well with the independent testing data sets, too. On the other hand, the representation using pixel intensities was stated as insufficient for classification using our approach.
Detekce bobulí v přirozeném prostředí pomocí dopředné vícevrstvé neuronové sítě jako klasifikátoru
Keywords: grape detection; neural networks; image processing; precision viticulture; detekce bobulí; neuronové sítě; zpracování obrazu; přesné vinohradnictví