An Image Matching Method Based on SIFT Feature
| Autor: | Zhong Hong Wu, Zhao Ming Shi, Yin Wen Dong, Bo Ying Geng |
|---|---|
| Rok vydání: | 2012 |
| Předmět: |
Matching (statistics)
Mahalanobis distance Similarity (geometry) business.industry Template matching ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Scale-invariant feature transform Pattern recognition General Medicine k-nearest neighbors algorithm Feature (computer vision) Point (geometry) Artificial intelligence business Mathematics |
| Zdroj: | Applied Mechanics and Materials. :2855-2859 |
| ISSN: | 1662-7482 |
| DOI: | 10.4028/www.scientific.net/amm.170-173.2855 |
| Popis: | Aiming at problems about repeat matching and wrong matching appeared when traditional SIFT algorithm was used in image matching, an image matching method based on SIFT feature was put forward. Firstly, SIFT features were extracted by traditional SIFT algorithm and candidate matching point pairs were obtained by the nearest neighbor rule. Secondly, lateral matching method was used to remove repeat matched dot-pairs. Finally, Mahalanobis distance as a similarity measurement was used to remove wrong matched dot-pairs. Experiment shows this method can achieve image matching effectively with high accuracy. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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