DOI QR코드

DOI QR Code

Object Recognition Using Hausdorff Distance and Image Matching Algorithm

Hausdorff Distance와 이미지정합 알고리듬을 이용한 물체인식

  • Kim, Dong-Gi (Dept. of Mechanical Design Engineering, Graduate School of Chungnam National University) ;
  • Lee, Wan-Jae (Dept. of Mechanical Design Engineering, Graduate School of Chungnam National University) ;
  • Gang, Lee-Seok
  • 김동기 (충남대학교 대학원 기계설계공학과) ;
  • 이완재 (충남대학교 대학원 기계설계공학과) ;
  • 강이석
  • Published : 2001.05.01

Abstract

The pixel information of the object was obtained sequentially and pixels were clustered to a label by the line labeling method. Feature points were determined by finding the slope for edge pixels after selecting the fixed number of edge pixels. The slope was estimated by the least square method to reduce the detection error. Once a matching point was determined by comparing the feature information of the object and the pattern, the parameters for translation, scaling and rotation were obtained by selecting the longer line of the two which passed through the matching point from left and right sides. Finally, modified Hausdorff Distance has been used to identify the similarity between the object and the given pattern. The multi-label method was developed for recognizing the patterns with more than one label, which performs the modified Hausdorff Distance twice. Experiments have been performed to verify the performance of the proposed algorithm and method for simple target image, complex target image, simple pattern, and complex pattern as well as the partially hidden object. It was proved via experiments that the proposed image matching algorithm for recognizing the object had a good performance of matching.

Keywords

Line Labeling;Multi Label;Feature Point;Matching Point

References

  1. Shepherd Tomas. S., Utta,l William, Dayanand, Sriram and Lovell, Robb, 1992, 'A Method for Shift, Rotation and Scale Invariant Pateern Recognition Using the Form and Arranement of Pattern Specific Feature,' Pattern Recognition, Vol. 25, No. 4, pp. 343-355 https://doi.org/10.1016/0031-3203(92)90084-V
  2. Spirkovska Lilly and Reid, Max, B., 1992, 'Robust Position, Scale, and Rotation Invariant Object Recognition Using Higher-order Neural Networks,' Pattern Recognition, Vol. 25, No. 9, pp. 975-985 https://doi.org/10.1016/0031-3203(92)90062-N
  3. Huttenlocher, Daniel, P., Kianderman, Gregory, A. and Rucklidge, William, J., 1993, 'Comparing Images Using the Hausdorff Distance,' IEEE Transaction on Pattern Analysis and Machine Intelligence, Vol. PAMI-15, No. 9, pp. 850-863 https://doi.org/10.1109/34.232073
  4. Sim, D. G., Kwon, O. K. and Park, R. H., 1999, 'Object Matching Algorithm Using Robust Hausdorff Distance Measures,' IEEE Transactions on Image Processing, Vol. 8, No. 3, pp. 425-429 https://doi.org/10.1109/83.748897
  5. 표창률, 김영진, 1997, '화상처리법을 이용한 A533B강의 진전균열특이장 평가,' 대한기계학회논문집(A), 제21권, 제1호, pp. 124-142
  6. Stein Fridtjof and Medioni Gerard, 1992 'Structural Indexing : Efficient 3-D Objest Recognition,' IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol. 14, No. 2, pp. 125-145 https://doi.org/10.1109/34.121785
  7. 장경영, 김병엽, 한창수, 박종현, 감도경, 1997, '머신비전을 이용한 SMD VR의 중심위치와 홈방향 정밀계측,' 대한기계학회 논문집(A), 제21권, 제8호, pp. 1339-1347
  8. 차주헌, 1997, '형상특징인식을 이용한 설계자료의 자동탐색,' 대한기계학회 논문집(A), 제21권, 제4호, pp. 634-645
  9. 남궁인, 1997, '장애물의 기하투영에 의한 일차매개곡선을 이용한 충동회피 경로계획,' 대한기계학회논문집(A), 제21권, 제12호, pp. 1992-2007
  10. Canny, J. F., 1986, 'A Computational Approach to Edge Detection,' IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol. 8, No. 6, pp. 679-698
  11. Zisserman Andrew, Forsyth David, Mundy Joseph, Rothwell Charlie, Liu Jane and Pillow Nic., 1995, '3-D Object Recognition Using Invariance,' AI Journal, Vol. 78, pp. 239-288 https://doi.org/10.1016/0004-3702(95)00023-2