Refined Extraction Method of Agricultural and Forestry Plot Boundaries Based on Yolov8n.

The shapes and scales of agricultural and forestry plots are quite different, making it challenging to extract refined boundaries. In order to extract refined boundaries of agricultural and forestry plots of different shapes and scales, a refined extraction method of agricultural and forestry plot boundaries based on Yolov8n was proposed. By enhancing the high-order nonconvex total variation model to reduce noise and preprocess the initial agricultural and forestry plot image, the edge detail information of the image is enhanced; the Yolov8n model is used to extract and fuse the multi-scale agricultural and forestry plot features of the processed image to obtain a multi-scale feature map. Based on this, the bounding boxes of plots of different scales are detected; combined with the fast active contour model, the edge details of the obtained multi-scale plot bounding boxes are further refined to obtain more refined boundaries of agricultural and forestry plots. The results show that this method can enhance the edge details of agricultural and forestry plot images through noise reduction processing, and achieve refined extraction of agricultural and forestry plot boundaries of various scales and shapes. The extracted boundaries can almost match the actual boundaries, and the average accuracy can reach 98%. The above can provide a guarantee for the rational allocation of resources for precision agriculture. [ABSTRACT FROM AUTHOR]