Extraction of Camellia oleifera crown width based on the method of optimized watershed with multi-scale markers.

Abstract

In view of the limitation of scale on the spatial structure of ground objects and the problem that traditional watershed segmentation tends to produce crown over-segmentation, we proposed a segmentation method of Camellia oleifera crown based on the optimized watershed with multi-scale markers, with the C. oleifera base in Mingyue Village of Changsha County as the research object. Firstly, the high-resolution unmanned aerial vehicle (UAV) was used to collect images. The image features were analyzed to construct the classification system of C. oleifera, and the distribution area of C. oleifera was extracted. After being extracted by multi-scale region iterative growth, the crown markers were applied to the multi-threshold scale watershed transformation. Combined with Johnson index, the optimal scale of crown marker growth and watershed threshold was used to realize the accurate identification of individual trees. The results showed that the relative error between the method of optimized watershed with multi-scale markers and the visual interpretation of the reference value of tree-crown was 9.4% for the separation of individual trees. The overall identification accuracy of each tree was 89.4%, which was 34.8% higher than that of the traditional watershed segmentation method. The optimal iterative growth scale obtained by Johnson index was 20, while the thre-shold scale of watershed segmentation was 85. Compared with the results of different scale combinations, the crown extraction accuracy under the optimal scale was the highest (R2=0.75). The method of optimized watershed with multi-scale markers could accurately separate C. oleifera crown. Applying this method to UAV image crown segmentation could effectively improve the efficiency of economic forest investigation.