With the rapid adoption of automatic guidance systems in agriculture, automated path planning has great potential to further optimize field operations. Field operations should be done in a manner that minimizes time and travel over field surfaces and should be coordinated with specific field operation requirements, machine characteristics, and topographical features of arable lands. To reach this goal, an intelligent coverage path planning algorithm is the key. To determine the full coverage pattern of a given field by using boustrophedon paths, it is necessary to know whether to and how to decompose a field into sub-regions and how to determine the travel direction within each sub-region. A geometric model was developed to represent this coverage path planning problem, and a path planning algorithm was developed based on this geometric model. The search mechanism of the algorithm was guided by a customized cost function resulting from the analysis of different headland turning types and implemented with a divide-and-conquer strategy. The complexity of the algorithm was analyzed, and methods for reducing the computational time are discussed. Field examples with complexity ranging from a simple convex shape to an irregular polygonal shape that has multiple obstacles within its interior were tested with this algorithm. The results were compared with other reported approaches or farmers' recorded patterns. These results indicate that the proposed algorithm was effective in producing optimal field decomposition and coverage path direction in each sub-region.