Abstract: In order to meet the requirements of intelligent recognition of field mulch film based on machine vision, the images were taken vertically by unmanned aerial vehicle (UAV) to the tobacco seedlings with mulch film in the field. The component color information histograms based on RGB and HSV color model of mulch film, tobacco seedlings and soil were analyzed. The color information of B component and V component was able to identify mulch film from background with the threshold segmentation method. The manual threshold segmentation, iterative threshold segmentation, large-law segmentation and maximum entropy method based on genetic algorithm were compared. Results showed that the iterative threshold segmentation algorithm had the highest target recognition rate of 71%, and the processing time was the shortest. The mulch film recognition rates under different flight heights was analyzed and figured out. It was found that the film recognition rate at 50 m flight height was the highest as 80.06%, the film recognition area was 246.83 m², and the film coverage rate was 30.12%. This research provided a method and reference for intelligent identification of mulch film and residual membrane with crop based on UAV.

Key words: unmanned aerial vehicle, field mulch film, threshold segmentation, recognition rate