Badr, Arash ShahbazArash ShahbazBadrPrapitasari, Luh Putu AyuLuh Putu AyuPrapitasariGrigat, Rolf-RainerRolf-RainerGrigat2021-06-112021-06-112015Proceedings of the 10th International Conference on Computer Vision Theory and Applications Vol. 3: 504-511 (2015)http://hdl.handle.net/11420/9737In this paper, a new feature matching algorithm is proposed and evaluated. This method makes use of features that are extracted by SIFT and aims at reducing the processing time of the matching phase of SIFT. The idea behind this method is to use the information obtained from already detected matches to restrict the range of possible correspondences in the subsequent matching attempts. For this purpose, a few initial matches are used to estimate the homography that relates the two images. Based on this homography, the estimated location of the features of the reference image after transformation to the test image can be specified. This information is used to specify a small set of possible matches for each reference feature based on their distance to the estimated location. The restriction of possible matches leads to a reduction of processing time since the quadratic complexity of the one-to-one matching is undermined. Due to the restrictions of 2D homographies, this method can only be applied to images that are related by pure-rotational transformations or images of planar object.enhttps://creativecommons.org/licenses/by-nc-nd/4.0/Image CorrespondencesFeature MatchingLocal Features, SIFTHomography EstimationInformatikConference Paper10.15480/882.360710.5220/000529610504051110.15480/882.3607Other