The Weed Plant Detection

The Knowledge about the distribution of weedswithin the sector could also be prerequisite for thesite-specific treatment. Optical sensors changes to detect varyweed densities and species which can have mapped using GPSdata. Weeds are extracted from the pictures that are using theimage processing and therefore the report by theform features. The classification supported the featuresreveal the type and therefore the number of weeds per theimage. For the classification the sole maximum of sixteenfeatures out of the eighty-one computed ones is employed.Which enables the optimal distinction of weed classes is usedthe choice is usually done using processing algorithms,which the speed discriminate of the features of prototypes. Ifno prototypes are available, clustering algorithms areoften used to automatically generate clusters. Within the nextstep weed classes are often assigned to the clusters. Suchprocedure aids to select prototypes, which are completedmanually. Classes are often identified, that are distinct withinthe feature space or which are overlapping, and thus not wellseparable. The clustering is usually utilized in some, lesscomplex cases to work out automatic procedure for theclassification. By using the system weed plants are generated.These are differentiating to the results of manual weeds sampling.