@article{(Open Science Index):https://publications.waset.org/pdf/10007607,
	  title     = {K-Means Based Matching Algorithm for  Multi-Resolution Feature Descriptors},
	  author    = {Shao-Tzu Huang and  Chen-Chien Hsu and  Wei-Yen Wang},
	  country	= {},
	  institution	= {},
	  abstract     = {Matching high dimensional features between images is computationally expensive for exhaustive search approaches in computer vision. Although the dimension of the feature can be degraded by simplifying the prior knowledge of homography, matching accuracy may degrade as a tradeoff. In this paper, we present a feature matching method based on k-means algorithm that reduces the matching cost and matches the features between images instead of using a simplified geometric assumption. Experimental results show that the proposed method outperforms the previous linear exhaustive search approaches in terms of the inlier ratio of matched pairs.
},
	    journal   = {International Journal of Electrical and Computer Engineering},
	  volume    = {11},
	  number    = {8},
	  year      = {2017},
	  pages     = {942 - 946},
	  ee        = {https://publications.waset.org/pdf/10007607},
	  url   	= {https://publications.waset.org/vol/128},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 128, 2017},
	}