| Author Name | Affiliation | | HUO Ju | Dept. of Electrical Engineering , Harbin Institute of Technology, Harbin 150001, China | | YANG Ning | Control and Simulation Center, Harbin Institute of Technology, Harbin 150080, China | | CAO Mao-yong | College of Information and Electrical Engineering, Shan Dong University of Science and Technology, Qingdao 266590, China | | YANG Ming | Control and Simulation Center, Harbin Institute of Technology, Harbin 150080, China |
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| Abstract: |
| A novel algorithm is presented to make the results of image matching more reliable and accurate based on SIFT (Scale Invariant Feature Transform). SIFT algorithm has been identified as the most resistant matching algorithm to common image deformations; however, if there are similar regions in images, SIFT algorithm still generates some analogical descriptors and provides many mismatches. This paper examines the local image descriptor used by SIFT and presents a new algorithm by integrating SIFT with two-dimensional moment invariants and disparity gradient to improve the matching results. In the new algorithm, decision tree is used, and the whole matching process is divided into three levels with different primitives. Matching points are considered as correct ones only when they satisfy all the three similarity measurements. Experiment results demonstrate that the new approach is more reliable and accurate. |
| Key words: image matching SIFT algorithm two-dimensional moment invariants disparity gradient |
| DOI：10.11916/j.issn.1005-9113.2012.04.015 |
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