Image matching is at the base of many computer vision problems, such as object recognition or image stitching. Standard SIFT provides poor performance when images under viewpoint change conditions and with similar corners. Hence, we propose a matching algorithm combine regional SSDA with simplified SIFT algorithm. We demonstrate through experiments that our algorithm yields better performance in images of viewpoint change and similar feature points. Besides, the simplified algorithm cut down about half the time was originally needed in our tested images.