전자공학회논문지 (Journal of the Institute of Electronics and Information Engineers)

  • 제53권6호
  • /
  • Pages.122-129
  • /
  • 2016
  • /
  • 2287-5026(pISSN)
  • /
  • 2288-159X(eISSN)
대한전자공학회 (The Institute of Electronics and Information Engineers)
권호 표지
DOI QR코드

DOI QR Code

패턴인식 필터링을 적용한 물체인식 성능 향상 기법

A Method for Improving Object Recognition Using Pattern Recognition Filtering

  • 투고 : 2015.07.31
  • 심사 : 2016.05.30
  • 발행 : 2016.06.25
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

컴퓨터 비전(Computer vision) 분야에서 물체인식을 위한 많은 알고리즘이 연구되고 있다. 그중 특징점(feature) 기반의 SURF(Speeded Up Robust Features) 알고리즘은 다른 알고리즘에 비해 속도와 정확도 면에서 우수하다. 하지만 SURF 알고리즘은 대응점 검출 시 대응점 오정합으로 물체인식에 실패하는 단점이 있다. 본 논문은 물체 인식률을 향상하기 위하여 SURF와 RANSAC(Random Sample Consensus) 알고리즘을 기반으로 물체인식 시스템을 구현하고, 패턴인식 필터링을 제안하였다. 또한, 실험을 통하여 물체 인식률 향상 결과를 제시하였다.

There have been a lot of researches on object recognition in computer vision. The SURF(Speeded Up Robust Features) algorithm based on feature detection is faster and more accurate than others. However, this algorithm has a shortcoming of making an error due to feature point mismatching when extracting feature points. In order to increase a success rate of object recognition, we have created an object recognition system based on SURF and RANSAC(Random Sample Consensus) algorithm and proposed the pattern recognition filtering. We have also presented experiment results relating to enhanced the success rate of object recognition.

키워드

참고문헌

  1. Herbert Bay, Tinne Tuytelaars, Luc Van Gool, "SURF : Speeded Up Robust Features", European Conference on Computer Vision 2006, Vol. 3951, pp. 404-417, May 2006.
  2. David G. Lowe, "Distinctive image features from scale-incaiant Key Point", International Journal of Computer Vision 2004, Vol. 60, Issue 2, pp. 91-110, Nov 2004.
  3. Ozuysal. M, Fua. P, Lepetit V, "Fast Keypoint Recognition in Ten lines of Code", Computer Vision and Pattern Recognition 2007, June 2007.
  4. Michael Calonder, Vincent Lepetit, Christoph Strecha, Pascal Fua, "BRIEF : Binary Robust Independent Elementary Features", European Conference on Computer Vision 2010, Vol. 6314, pp. 778-792, Sep 2010.
  5. Ethan Rublee, Vincent Rabaud, Kurt Konolige, Gary Bradski, "ORB : an efficient alternative to SIFT or SURF", International Conference on Computer Vision 2011, pp. 2564-2571, Nov 2011.
  6. Edward Rosten, Tom Drummond, "Machine Learning for High-Speed Corner Detection", European Conference on Computer Vision 2006, Vol. 3951, pp. 430-443, 2006.
  7. Fishler, Martin A, Bolles, Robert C. "Random sample consensus : A paradigm for model fitting with applications to image analysis and automated cartography", Communications of the ACM, Vol. 24, pp. 381-395, June 1981. https://doi.org/10.1145/358669.358692
  8. Richard Hartley, Andrew Zisserman, "Multiple View Geometry", 2nd Edition, Cambridge University Press, p25-44, 2004