An Image Matching Algorithm Based on Combination of SIFT and the Rotation Invariant LBP

SIFT(scale invariant feature transform)is one of the most robust and the widely used image matching algorithms based on local features.However,its computational complexity is high.Aiming at speeding up the SIFT computation,we present an image matching algorithm by combining SIFT and the rotation-invariant LBP(local binary patterns).Firstly,two sets of keypoints are extracted from the two images for matching by applying the SIFT algorithm;Secondly,each keypoint is described by the rotation-invariant LBP patterns,which are computed from the image patch centered at the keypoint;Finally,the matching pairs between the two sets of keypoints are determined by using the nearest neighbor distance ratio based matching strategy.The experimental results show that the proposed SIFT+LBP algorithm is more rapid than the standard SIFT algorithm while the performance is favorably compared to the standard SIFT algorithm when matching among structured scene images.