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In studies on agricultural robot vision systems, data used to evaluate algorithm performance, such as successful recognition rates, vary because of various factors. If the variation is too large, representation of the actual performance of algorithms by the data is bound to be poor. Here we present a method for analysing the quality of data used to evaluate the performance of a recognition algorithm...
The accuracy of the three dimensional localization of the vision systems of harvesting robots is likely to be effected by the occlusion of leaves and branches. To quantitatively analyze the influence to the localization for tomatoes based on binocular stereo vision caused by the occlusion, we analyzed the three dimensional localization errors of occluded tomatoes in three kinds of occlusion degree...
To realize the automation of harvesting work, automatic recognition of fruits and vegetables should be realized firstly. In the researches on the recognition of fruits and vegetables, the recognition of occluded fruits and vegetables is a difficult point. This paper presents a recognition algorithm for occluded tomatoes based on circle regression. It mainly bases on the principle that there is a big...
Recognition of clustered fruits and vegetables is a most challenging subject in researches on the vision system of harvesting robot. A recognition algorithm for clustered tomatoes based on mathematical morphology was tested. This algorithm mainly included four steps. First, tomato image segmentation was realized based on a normalized color difference. Second, clustered region could be recognized according...
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