The block-matching motion estimation algorithm using a translational motion model cannot provide acceptable image quality in low bit-rate coding. To improve coding performance, we can use image warping using affine transformation as a more complicated motion model than the translational motion model. However, when some node points are flipped over in the image warping method, it creates severe deformations of the mesh structure and brings image degradations. It also requires large computational complexity. We show that wide search ranges do not always improve reconstructed image quality due to the large deformation of meshes. We analyze optimal search ranges according to frame difference and decide variable search ranges adaptively to get a motion vector at each node point. Since the block with a larger error than a threshold makes a large distortion, we give higher priority during motion estimation at a certain rate. To reduce computational complexity, we also introduce an adaptive partial matching method instead of applying the hexagonal matching method on the whole image. As a result, we develop an effective image warping method in terms of computational complexity, reasonable reconstructed image quality, and fewer number of coding bits.