To address the difficulty of locating the picking point of a tea sprout during the intelligent automatic picking of famous tea,this study proposes a method to obtain information on the picking point on the basis of th...To address the difficulty of locating the picking point of a tea sprout during the intelligent automatic picking of famous tea,this study proposes a method to obtain information on the picking point on the basis of the ShiTomasi algorithm.This method can rapidly identify a tea sprout’s picking point and obtain its coordinates.Images of tea sprouts in a tea garden were collected,and the G-B component of tea sprouts was segmented using the Otsu algorithm.The region of interest was set with the lowest point of its contour as the center.The characteristics of tea buds and branches in the area were extracted,and the Otsu algorithm was used for a second segmentation of tea sprout images.The tea buds were segmented using the improved Zhang algorithm.The branch feature binary image was used to refine the skeleton,and the Shi-Tomasi algorithm was used to detect the corners of the skeleton and calculate and mark the picking points of the shoots.Sixty sets of samples were tested.The test identified 1,042 effective shoots for tender buds,and 887 picking points were marked,with a success rate of 85.12%,thereby verifying the effectiveness of the method and providing a theoretical reference for the visual positioning of the automatic picking of famous tea.展开更多
基金The authors gratefully acknowledge the financial support provided by the Special Fund for the Construction of Modern Agricultural Industrial Technology Systems(CARS-19)in China.
文摘To address the difficulty of locating the picking point of a tea sprout during the intelligent automatic picking of famous tea,this study proposes a method to obtain information on the picking point on the basis of the ShiTomasi algorithm.This method can rapidly identify a tea sprout’s picking point and obtain its coordinates.Images of tea sprouts in a tea garden were collected,and the G-B component of tea sprouts was segmented using the Otsu algorithm.The region of interest was set with the lowest point of its contour as the center.The characteristics of tea buds and branches in the area were extracted,and the Otsu algorithm was used for a second segmentation of tea sprout images.The tea buds were segmented using the improved Zhang algorithm.The branch feature binary image was used to refine the skeleton,and the Shi-Tomasi algorithm was used to detect the corners of the skeleton and calculate and mark the picking points of the shoots.Sixty sets of samples were tested.The test identified 1,042 effective shoots for tender buds,and 887 picking points were marked,with a success rate of 85.12%,thereby verifying the effectiveness of the method and providing a theoretical reference for the visual positioning of the automatic picking of famous tea.
