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Unmanned operation of grain harvesting machinery can address the issue of labour shortage effectively during the harvesting season. The whole-field automatic navigation is a significant indicator of intelligent unmanned harvester. To address the issue of automatic dotting for unmanned rice harvesting, the automatic navigation of the outermost circle of the rice field was realized based on cut boundary fitting and headland region detection. The trajectory of rice harvester was recorded by using Beidou real-time kinematic (RTK) while working in the outermost circle of the paddy field, which enabled automatic dotting for the remaining operation region (ROR). A dynamic region of interest was constructed by employing the priori morphology knowledge of the target area, which not only improved the robustness of cut boundary fitting but also reduced its computational complexity. Once the rice harvester entered the headland region, the uncut boundary in the front of the machinery was extracted and the intersection point between two uncut boundary lines was fixed. Finally, the position of the vertex corresponding to the ROR was calculated based on the antenna position and operating width. The proposed method was verified based on an automated trolley, and results indicated that the average straight line tracking error was 4.1cm, and the maximum tracking error was 6.3cm at speed of 0.8m/s. The processing time for single image was less than 50ms. The average error of automatic dotting was 3.5cm, and it can realize automatic dotting of rice field of right-angled trapezoid. It can be concluded that the designed automatic dotting system satisfied the needing of whole-field unmanned operation of rice harvester.