摘要:Precision agriculture is a mode of modern agricultural production and management on the basis of information technology, and it is an important way to achieve low consumption, high efficiency, fine quality and safety in agriculture. Moreover, accurate recognition and extraction of field operation area (FOA) boundary is a crucial basic data to implement precision agriculture. Due to the irregular shape, different planting ways and inconsistent size of FOA, it is difficult to recognize and extract the boundary. Therefore, the boundary of FOA based on UAV remote sensing images was classified in this paper, and a priori rule was proposed according to the boundary characteristics. Combined with the classical algorithm of image processing, a boundary recognition and extraction system was developed by LabVIEW to obtain the effective boundary of FOA. At last, the boundary recognition method and the accuracy and real-time performance of the extraction system were tested, and the result shows the method and system can accurately recognize and extract the actual boundary of FOA, and they are adapted to three different types of boundaries and image resolutions. The system has good real-time performance, and the single-frame image processing time does not exceed 100ms when the image resolution is lower than 1920⁎1280.