This paper presents a rapid method to align large sets of 3D scanned data automatically. The method incorporates the technique of image registration into the pair-wise registration. Firstly, it retrieves two texture images from the scanned data to align. A method is proposed to generate the texture image from the range image when scanned data do not contain the texture information. Secondly, it detects the features using SIFT (scale-invariant feature transform) on texture images, and a set of potential corresponding pixels is selected by means of pre-filter and cross validation. Then a matching algorithm, based on RANSAC (random sample consensus) algorithm, is applied to specify the matching pixel pairs between two images. All matches obtained are mapped to 3D space and used to estimate the rigid transformation. Finally, a modified ICP (iterative closest point) algorithm is applied to refine the result. The paper also presents a method to create model graph rapidly for multi-view registration which avoids aligning all pairs of range images. This reconstruction technique achieves a robust and high performance in the application of automatic rebuilding 3D models of culture heritages.