Research on fruit sorting system based on machine vision
In view of the huge volume and low efficiency of the fruit sorting equipment in the market,a novel fruit sorting system is designed in this paper.In the designed system,the apples are taken as the testing samples.The RGB(red,green,blue)images taken by camera are converted into HSV(hue,saturation,value)images.The grades of the apple colors are calculated according to the H component distribution.The Canny edge detection algorithm is used to extract the apple contours.The minimum circumferential circle method is used to calculate the apple diameters.The apples are graded by the parameters of their color grades and diameters.The system testing shows that the colors and sizes of the samples are consistent with those of the apples,and the error between the fruit diameter obtained by sorting equipment and that by manual sorting is within±1.35 mm.In conclusion,the system can realize the goals of precise sorting and automatic operation,so it can improve the sorting accuracy and efficiency.
machine visionfruit sortingHSV color modelCanny edge detection algorithmcontour extractionminimum circumferential circle method