An algorithm for finding coupling points plays an important role in the Iterative Closest Point algorithm(ICP) which is widely used in registration applications in medical and 3-D architecture areas. In recent researches of finding coupling points, Approximate K-D tree search algorithm (AK-D tree) is an efficient nearest neighbor search algorithm with comparable results. We proposed Adaptive Dual AK-D tree search algorithm (ADAK-D tree) for searching and synthesizing coupling points as significant control points to improve the registration accuracy in ICP registration applications. ADAK-D tree utilizes AK-D tree twice in different geometrical projection orders to reserve true nearest neighbor points used in later ICP stages. An adaptive threshold in ADAK-D tree is used to reserve sufficient coupling points for a smaller alignment error. Experimental results are shown that the registration accuracy of using ADAK-D tree is improved more than the result of using AK-D tree and the computation time is acceptable.