Journal of the Korea Academia-Industrial cooperation Society (한국산학기술학회논문지)

The Korea Academia-Industrial cooperation Society (한국산학기술학회)
권호 표지
DOI QR코드

DOI QR Code

Target Object Detection Based on Robust Feature Extraction

강인한 특징 추출에 기반한 대상물체 검출

  • 장석우 (안양대학교 디지털미디어학과) ;
  • 허문행 (안양대학교 디지털미디어학과)
  • Received : 2014.07.31
  • Accepted : 2014.12.11
  • Published : 2014.12.31
Download PDF
⟨ Previous Next ⟩

Abstract

Detecting target objects robustly in natural environments is a difficult problem in the computer vision and image processing areas. This paper suggests a method of robustly detecting target objects in the environments where reflection exists. The suggested algorithm first captures scenes with a stereo camera and extracts the line and corner features representing the target objects. This method then eliminates the reflected features among the extracted ones using a homographic transform. Subsequently, the method robustly detects the target objects by clustering only real features. The experimental results showed that the suggested algorithm effectively detects the target objects in reflection environments rather than existing algorithms.

특정한 제한을 두지 않는 복잡한 자연환경에서 사용자가 원하는 목표 물체만을 정확하게 검출하는 작업은 컴퓨터 비전 및 영상처리 분야에서 중요하지만 매우 어려운 문제 중의 하나이다. 본 논문에서는 반사가 존재하는 여러 환경에서 목표하는 물체를 강인하게 검출하는 새로운 방법을 제안한다. 제안된 방법에서는 먼저 스테레오 카메라를 이용하여 목표 물체를 촬영한 다음, 물체를 가장 잘 표현하는 라인과 코너 특징들을 추출한다. 그런 다음, 촬영된 좌우 영상으로부터 호모그래픽 변환을 이용하여 실제로 존재하지 않는 반사된 특징들을 효과적으로 제거한다. 마지막으로, 반사된 특징들을 제거한 실제 특징들만을 군집화하여 대상 물체만을 강건하게 검출한다. 본 논문의 실험결과에서는 제안된 알고리즘이 기존의 알고리즘에 비해서 반사가 존재하는 자연 환경에서 목표 물체를 보다 강인하게 검출한다는 것을 보여준다.

Keywords

References

  1. C.-H. Chuang, S.-C. Cheng, C.-C. Chang, Y.-.P Phoebe Chen, "Model-based Approach to Spatial-Temporal Sampling of Video Clips for Video Object Detection by Classification," Journal of Visual Communication and Image Representation, Vol. 25, Issue 5, pp. 1018-1030, July 2014. DOI: http://dx.doi.org/10.1016/j.jvcir.2014.02.014
  2. M.-C. Yeh, C.-F. Hsu, and C.-J. Lu, "Fast Salient Object Detection through Efficient Subwindow Search," Pattern Recognition Letters, Vol. 46, pp. 60-66, September 2014. DOI: http://dx.doi.org/10.1016/j.patrec.2014.05.006
  3. J. M. Choi, H. J. Chang, Y. J. Yoo, and J. Y. Choi, "Robust Moving Object Detection against Fast Illumination Change," Computer Vision and Image Understanding, Vol. 116, Issue 2, pp. 179-193, February 2012. DOI: http://dx.doi.org/10.1016/j.cviu.2011.10.007
  4. D. Muselet and L. Macaire, "Combining Color and Spatial Information for Object Recognition across Illumination Changes," Pattern Recognition Letters, Vol. 28, Issue 10, pp. 1176-1185, July 2007. DOI: http://dx.doi.org/10.1016/j.patrec.2007.02.001
  5. H. Zhao, G. Qin, and X. Wang, "Improvement of Canny Algorithm Based on Pavement Edge Detection," In Proc. of the International Congress on Image and Signal Processing (CISP), Vol. 2, pp. 964-967, 2010. DOI: http://dx.doi.org/10.1109/CISP.2010.5646923
  6. G. Sun, Q. Liu, Q. Liu, C. Ji, and X. Li, "A Novel Approach for Edge Detection based on the Theory of Universal Gravity," Pattern Recognition, Vol. 40, Issue 10, pp. 2766-2775, October 2007. DOI: http://dx.doi.org/10.1016/j.patcog.2007.01.006
  7. H.-I. Choi, Computer Vision, Hongrung Publishing Company, pp. 96-104, November 2012.
  8. L. Chen, W. Lu, J. Ni, W. Sun, and J. Huang, "Region Duplication Detection Based on Harris Corner Points and Step Sector Statistics," Journal of Visual Communication and Image Representation, Vol. 24, Issue 3, pp. 244-254, April 2013. DOI: http://dx.doi.org/10.1016/j.jvcir.2013.01.008
  9. B. Zhang and Y. F. Li, "An Efficient Method for Dynamic Calibration and 3D Reconstruction Using Homographic Transformation," Sensors and Actuators A: Physical, Vol. 119, Issue 2, pp. 349-357, April 2005, DOI: http://dx.doi.org/10.1016/j.sna.2004.10.013
  10. R. Hartley and A. Ziserman, Multiple View Geometry in Computer Vision, Cambridge University Press, Second Edition, 2006.
  11. M.-H. Jo, "A Study on the Extraction of a River from the RapidEye Image Using ISODATA Algorithm," Journal of the Korean Association of Geographic Information Studies, Vol. 15, No. 4, pp. 1-14, October 2012. DOI: http://dx.doi.org/10.11108/kagis.2012.15.4.001
  12. Q. Liu, Z. Zhao, Y.-X. Li, and Y. Li, "Feature Selection Based on Sensitivity Analysis of Fuzzy ISODATA," Neurocomputing, Vol. 85, pp. 29-37, May 2012. DOI: http://dx.doi.org/10.1016/j.neucom.2012.01.005