Open Access
| Issue |
MATEC Web of Conferences
Volume 59, 2016
2016 International Conference on Frontiers of Sensors Technologies (ICFST 2016)
|
|
|---|---|---|
| Article Number | 08001 | |
| Number of page(s) | 5 | |
| Section | Image processing | |
| DOI | https://doi.org/10.1051/matecconf/20165908001 | |
| Published online | 24 May 2016 | |
- L. Zhou, Y. Zhang, Y. Sun, T. Liang, and S. Lu, “Development and application of equipment inspection robot for smart substation,” Automation of Electric Power Systems, 35, 85-88, (2011). [Google Scholar]
- H. Zhang, W. Wang, L. J. Xu, H. Qin, and M. Liu, “Application of image recognition technology in electrical equipment on-line monitoring,” Power System Protection and Control, 38 (2010). [Google Scholar]
- L. Li, P. Li, M. Yang, B. Zheng, and B. H. Wang, “Research on abnormal appearance detection approach of electric power equipment,” Optics and Optoelectronic Technology, 8 (2010). [Google Scholar]
- M. Brown, and D. G. Lowe, “Automatic panoramic image stitching using invariant features,” International Journal of Computer Vision, 74(2007). [Google Scholar]
- E. Rublee, V. Rabaud, K. Konolige, and G. Bradski, “ORB: an efficient alternative to SIFT or SURF,” Proc.13th Computer Vision Conf, 2564-2571, (2011). [Google Scholar]
- B. Ko and J. Nam, “Object-of-interest image segmentation based on human attention and semantic region clustering,” Journal of the Optical Society of America, 23 (2006). [Google Scholar]
- T. Judd, K. Ehinger, F. Durand, and A. Torralba, “Learning to Predict Where Humans Look,” Proc.12th Computer Vision Conf, Kyoto (2009). [Google Scholar]
- T. Chen, M. M. Cheng, P. Tan, A. Shamir, and S.M. Hu, “Sketch2photo: Internet image montage,” ACM Trans, 28 (2009). [Google Scholar]
- R. Achanta, F. Estrada, P. Wils, and S. Sabine, “Salient region detection and segmentation,” Proc. 6th Computer Vision Systems Conf., 66-75, (2008). [Google Scholar]
- B. Herbert, A. Ess, T. Tinne, and G. L. Van, “SURF: speeded up robust features,” Computer Vision and Image Understanding, 110 (2008). [Google Scholar]
- M. A. Fischer and R. C. Bolles, “Random sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography,” Communications of the ACM, 24 (1981). [Google Scholar]
- L. Bruzzone, and D. F. Prieto, “An adaptive semiparametric and context-based approach to unsupervised change detection in multitemporal remote-sensing images,” IEEE Trans. On Image Processing, 11 (2002). [Google Scholar]
- A. Huertas and R. Nevatia, “Detecting changes in aerial views of man-made structures,” Image and Vision Computing, 18 (2000). [Google Scholar]
- M. K. Hu, “Visual pattern recognition by moment invariants,” IRE Trans. on Information Theory, 8(1962). [Google Scholar]
- J. Yang, Y. Shi, J. Yang, and L. Jiang, “A novel finger-vein recognition method with feature combination,” Proc. IEEE International Conference on Image Processing, 2709-2712, (2009). [Google Scholar]
- N. Dalal, and B. Triggs, “Histograms of oriented gradients for human detection,” Proc. IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 886-893, (2005). [Google Scholar]
- X. Zhang and F. Fang, “Multivariate statistical introduction,” Sciences Press, 16 (1999). [Google Scholar]
- D. R. Hardoon, S. Szedmak, O. Szedmak, and J. Shawe-Taylor, “Canonical correlation analysis: an overview with application to learning methods,” Neural Computation, 16(2004). [Google Scholar]
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