Browse > Article
http://dx.doi.org/10.9708/jksci.2014.19.11.043

The Target Detection and Classification Method Using SURF Feature Points and Image Displacement in Infrared Images  

Kim, Jae-Hyup (Samsung Thales Co.)
Choi, Bong-Joon (Samsung Thales Co.)
Chun, Seung-Woo (Samsung Thales Co.)
Lee, Jong-Min (Dept. of CSE, Hanyang University)
Moon, Young-Shik (Dept. of CSE, Hanyang University)
Abstract
In this paper, we propose the target detection method using image displacement, and classification method using SURF(Speeded Up Robust Features) feature points and BAS(Beam Angle Statistics) in infrared images. The SURF method that is a typical correspondence matching method in the area of image processing has been widely used, because it is significantly faster than the SIFT(Scale Invariant Feature Transform) method, and produces a similar performance. In addition, in most SURF based object recognition method, it consists of feature point extraction and matching process. In proposed method, it detects the target area using the displacement, and target classification is performed by using the geometry of SURF feature points. The proposed method was applied to the unmanned target detection/recognition system. The experimental results in virtual images and real images, we have approximately 73~85% of the classification performance.
Keywords
Target Detection; Target Classification; Image Registration; Image Displacement; SURF; BAS(Beam Angle Statistics);
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
연도 인용수 순위
1 D. Lowe, "Distinctive Image Features from Scale-Invariant Keypoints," International Journal of Computer Vision ,Vol. 60, no. 2, pp. 91-110, 2004.   DOI   ScienceOn
2 Jae Hyup Kim, Gyu Hee Park, Jun Ho Jeong, and Young Shik Mood, "Gunnery Classification Method using Shape Feature of Profile and GMM," Journal of IEEK CI, Vol. 48, No. 5, pp. 16-23, Nov. 2011.   과학기술학회마을
3 Sun-Gu Sun, Hyun Wook Park, "Automatic Target Recognition by selecting similarity-transform- invariant local and global features," Journal of IEEK SP, Vol. 3, No. 4, pp. 10-20, July 2002.
4 K. Mikolajczyk and C. Schmid, "A performance evaluation of local descriptors," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 27, no. 10, pp. 1615-1630, 2005.   DOI   ScienceOn
5 H. Bay, T. Tuytelaars, and L. V. Gool, "Surf: Speeded up robust features," Proc. of European Conference on Computer Vision, Vol. 3951, pp. 404-417, 2006.
6 D. Lowe, "Object recognition from local scale-invariant features", Proc. of ICCV, 1999.
7 H. Bay, Beat Fasel, and Luc Van Gool, "Interactive museum guide: Fast and robust recognition of museum objects," Proc. of First International Workshop on Mobile Vision, 2006.
8 M. Cummins and P. Newman, "FAB-MAP: Probabilistic Localization and Mapping in the Space of Appearance," International Journal of Robotics Research, Vol. 27, No. 6, pp. 647-665, 2008.   DOI   ScienceOn
9 H. Tamimi, H. Andreasson, A. Treptow, T.Duckett, and A. Zell, "Localization of mobile robots with omnidirectional vision using particle filter and iterative SIFT," Proc. of 2nd European Conf. on Mobile Robots(ECMR'05), September 2005.
10 A. C. Murillo, J. J. Guerrero, and C. Sagues, "SURF Features for Efficient Robot Localization with Omnidirectional Images," Proc. of IEEE Int'l Conf. on Robotics and Automation, pp. 3901-3907, 2007.
11 S. Se, D. Lowe, and J. Little. "Vision-based mobile robot localization and mapping using scale-invariant feature," Proc. of the International Conference on Robotics & Automation(ICRA), 2001.
12 Hyunsup Yoon, Youngjoon Han, and Hernsoo Hahn, "Extended SURF Algorithm with Color Invariant Feature and Global Feature," Journal of IEEK SP, Vol. 46, No. 6, pp. 58-67, Nov. 2009.   과학기술학회마을
13 Minku Kang, Wonkook Choo, and Seungbin Moon, "Face Recognition based on SURF Interest Point Extraction Algorithm," Journal of IEEK CI, Vol. 48, No. 3, pp. 58-67, May 2011.
14 P. A. Viola and M. J. Jones, "Rapid object detection using a boosted cascade of simple features," Proc. of CVPR, pp. 511-518, 2001.
15 J. Shi and C. Tomasi, "Good Features to Track," Proc. of Computer Vision and Pattern Recognition, pages 593-600, 1994.
16 C. Harris and M.J. Stephens, "A combined corner and edge detector," In Alvey Vision Conference, pp. 147-152, 1988.
17 N. Arica et al, "BAS: a perceptual shape descriptor based on the beam angle statistics," Pattern Recognition Letters, Vol. 24, pp. 1627-1639, 2003.   DOI   ScienceOn
18 Young-Gu Lee and Woo-Seung Choi, "Learning Networks for Learning the Pattern Vectors Causing Classification Error," Journal of KSCI, Vol. 10, No. 5, pp. 77-86, Nov. 2005.   과학기술학회마을
19 Kwang Seong Kim and Doosung Hwang, "Support Vector Machine Algorithm for Imbalanced Data learning," Journal of KSCI, Vol. 15, No. 7, pp. 11-17, July 2010.   과학기술학회마을   DOI   ScienceOn
20 S. K. Kang, Y. U. Kim, I. M. So, and S. T. Jung, "Enhancement of the Correctness of Marker Detection and Marker Recognition based on Artificial Neural Networks," Journal of KSCI, Vol. 13, No. 1, pp. 89-97, Jan. 2008.