Feature Point Extraction Method of X-Ray Image Based on Scale Invariant
| Autor: | Hong Liang, Si Qing Zhang, Yan Wei Wang, Yan Ming Pan, Bing Lin |
|---|---|
| Rok vydání: | 2013 |
| Předmět: |
Harris affine region detector
business.industry Feature extraction ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Pattern recognition General Medicine Scale space symbols.namesake Feature (computer vision) Computer Science::Computer Vision and Pattern Recognition Gaussian function symbols Affine transformation Pyramid (image processing) Artificial intelligence business Mathematics Feature detection (computer vision) |
| Zdroj: | Applied Mechanics and Materials. 274:667-670 |
| ISSN: | 1662-7482 |
| DOI: | 10.4028/www.scientific.net/amm.274.667 |
| Popis: | Feature Point Extraction Method of X-ray Image Based on Scale Invariant is proposed in this paper for industrial X-ray image with low contrast and some artifacts. First of all, the scale transformation of original image is adopted by the Gaussian kernel to building the DOG multi-scale pyramid. Then, the location and scale of the key points is fixed by the three-dimensional quadratic function. Finally, the Simply SIFT descriptor illustrates the key points. Experimental results show that the algorithm has good stability in translation, rotation and affine transformation, especially with 10 percent normalized Gaussian noise, this algorithm can still be detected feature points accuracy. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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