Feature Point Extraction Method of X-Ray Image Based on Scale Invariant


Article Preview

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.



Edited by:

Junpeng Shao and Xianli Liu




Y. W. Wang et al., "Feature Point Extraction Method of X-Ray Image Based on Scale Invariant", Applied Mechanics and Materials, Vol. 274, pp. 667-670, 2013

Online since:

January 2013




[1] C. Harris, M.Stephens, A combined corner and edge, Proceedings Fourth Alvey Vision Conference,Manchester,UK(1988)147-151.

[2] X.H. Zhang, B. Li; D. Yang, Novel Harris multi-scale corner detection algorithm. Journal of Electronics and Information Technology, Commun. 29(2007) 1735-1738, Language: Chinese.

[3] C.G. Guo, X.L. Li,L.F. Zhong,X. Luo, A fast and accurate corner detector based on Harris algorithm, 3rd International Symposium on Intelligent Information Technology Application, IITA (2009) 49-52.

DOI: https://doi.org/10.1109/iita.2009.311

[4] G.A.F. Thomas. Min-cut based segmentation of point clouds. 2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops (2009) 39-46.

DOI: https://doi.org/10.1109/iccvw.2009.5457721

[5] Q.L. Jiang, Edge Detection for Color Image Based on CNN, Advances in Information Sciences and Service Sciences, Commun. 3 (2011) 61-69.

[6] Y.Y. Gao H.G. Zhang,J. Guo, A novel keypoint detection in wavelet pyramid space, International Journal of Digital Content Technology and its Applications, Commun. 5(2011)55-62.

DOI: https://doi.org/10.4156/jdcta.vol5.issue6.8

[7] M.L. Wen,Y. Li,Q. Zhuo W.Y. Wang, Novel scale-invariant keypoint detector, Optical Engineering, Commun. 47(2008)1-6.

[8] D.G. Lowe, Distinctive image features from scale-invariant keypoints, International Journal of Computer Vision, Commun. 60(2004)91-110.

DOI: https://doi.org/10.1023/b:visi.0000029664.99615.94

[9] J.S. Krizaj, N. Pavešic, Adaptation of SIFT features for robust face recognition, Lecture Notes in Computer Science, Commun. 6111(2010) 394-404.

DOI: https://doi.org/10.1007/978-3-642-13772-3_40