亚洲一区欧美在线,日韩欧美视频免费观看,色戒的三场床戏分别是在几段,欧美日韩国产在线人成

Cucumber plug seedlings usually grow at different speeds in the growth process. In order to make the cucumber plug seedlings in the unified growth stage before leaving the factory, it is necessary to detect late emergence seedlings. An automatic detection method for late emergence of plug seedlings was proposed based on point cloud processing.The RGB-D camera was used to build the point cloud collection platform for plug seedlings. Through conditional filtering, statistical filtering and Euclidean clustering, the point cloud of plug seedling leaves could be segmented. Adopting α-shape algorithm calculation, and then the leaf area of plug seedlings was calculated by fitting method. Average error between the fitting value and the true value was 0.75cm2, and average relative error was 8.51%. The method of locating the seedling stem top positions based on the principal curvature was used to automatically obtain the plant height. The average error between the true values and the calculated values of plant height was 0.359cm, and the average relative error was 9.32%. The product of leaf area and plant height was used as the grading coefficient, and the value of subtracting the standard deviation from the mean value of the current seedling grading was used as the threshold for the classification of late emergence seedlings, so as to realize the automatic detection of late emergence seedlings in the plug tray. Comparing the calculated grading coefficient with the total fresh weight of seedlings, the change trend of the two was basically the same (little difference). The grading coefficient of late emergence seedlings with small total fresh weight was significantly lower than that of other normal seedlings. The proposed grading coefficient can effectively describe the growth of seedlings. The results showed that the success rate of the automatic detection method for late emergence seedlings in plug trays based on point cloud processing reached 95%, which can provide technical support for the detection of seedlings in industrial.