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多尺度模糊加权角点检测新算法研究 被引量：1

Multi-scale fuzzy weighted corner detection algorithm
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摘要 为了提高图像角点检测的准确度和降低噪声对检测效果的影响,将多尺度思想和模糊理论引入到角点检测过程中,在建立了像素点属于角点的隶属度函数的基础上提出一种多尺度模糊加权角点检测新算法.首先将原始图像使用高斯核函数进行变换生成一组响应图像,并将其进行加权叠加得到原始图像的平均角点响应值;再选取合适的阈值进行相关处理得到最终的角点.实验结果表明,该算法不但抗噪性能较好,而且提取出来的角点也较准确. In order to improve the detection accuracy of image corners and reduce the noise influence for detection performance, a multi-scale fuzzy weighted corner detection algorithm is proposed after building the membership function which determines whether pixel belongs to corner in this paper. The corner detection algorithm combines the idea of multi-scale and fuzzy theory. Firstly, the original image is transformed by using Gauss kernel function and a group of responsive images are got. The responsive images are superposed and weighed and the average corner responsive datas are got. Then the final corners are got after correlative processed by using selected appropriate threshold value. Experimental results show that the proposed method can not only resist noise effectively, but also detect corners successfully.
作者 乔晓芳 吴小俊 王士同 杨静宇
机构地区 江南大学信息工程学院 南京理工大学计算机科学与技术学院
出处 《控制与决策》 EI CSCD 北大核心 2009年第2期305-308,312,共5页 Control and Decision
基金 2006年教育部新世纪优秀人才计划项目(NCET20620487) 国家自然科学基金项目(60472060,60572034) 江苏省自然科学基金项目(BK2006081) 江南大学创新团队建设计划项目(JNIRT0702)
关键词 角点 角点检测 多尺度 模糊理论 Corners Corner detection Multi-scale Fuzzy theory
分类号 TP301.6 [自动化与计算机技术—计算机系统结构]
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参考文献9

  • 1陶茂垣,卢正鼎,袁武钢,凌贺飞,邹复好.基于图像尺度空间的几何不变特征点提取算法[J].电子学报,2006,34(B12):2564-2568. 被引量：8
  • 2He X C, Yung N H C. Curvature scale space corner detector with adaptive threshold and dynamic region of support [ C ]. Int Conf on Pattern Recognition. Cambridge: Institute of Electrical and Electronics Engineers Ine, 2004: 791-794.
  • 3Mokhtarian F, Suomela R. Curvature scale space for image point feature detection[C]. Seventh Int Conf on Image Processing and Its Applications. Manchester: Institution of Electrical Engineers, 1999:206-201.
  • 4Matsopoulos G, Marshall S. Feature migrateonin morphological scale space[C]. 1993 IEEE Int Conf on Acoustics, Speech, and Signal Processing. New York: Institute of Electrical and Electronics Engineers, 1993: 599-602.
  • 5陈白帆,蔡自兴.基于尺度空间理论的Harris角点检测[J].中南大学学报（自然科学版）,2005,36(5):751-754. 被引量：79
  • 6张剑清,潘励,王树根.摄影滴量学[M].武汉:武汉大学出版社,2003:83-85.
  • 7Charris M S. A combined corner and wine detectors[C]. Proc of the 4th Alvey Vision Conf. Manchester: The Plessey Company, 1988: 147-151.
  • 8Lindebern T. Feature detection with automatic scale selection[J]. Int J of Computer Vision, 1998, 30(2). 79-116.
  • 9Mikolajczyk K, Schmid C. Scale and affine invariant interest point detectors[J]. Int J of Computer Vision, 2004, 60(1): 63-86.

二级参考文献23

  • 1陈白帆,蔡自兴.基于尺度空间理论的Harris角点检测[J].中南大学学报（自然科学版）,2005,36(5):751-754. 被引量：79
  • 2Mokhtarian F, Suomela R. Robust image corner detection through curvature scale space[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1998, 20(12): 1376-1381.
  • 3Pikaz A, Dinstein I. Using simple decomposition for smoothing and feature point detection of noisy digital curves[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1994, 16(8): 808-813.
  • 4Harris C, Stephens M. A combined corner and edge detector[A]. Matthews M M. Proceedings of the Fourth Alvey Vision Conference[C]. Manchester: the University of Sheffield Printing Unit, 1988. 147-151.
  • 5Deriche R, Giraudon G. A computational approach for corner and vertex detection[J]. International Journal of Computer Vision, 1993, 10(2): 101-124.
  • 6Baker S, Nayar S K, Murase H. Parametric feature detection[J]. International Journal of Computer Vision, 1998, 27(1): 27-50.
  • 7Parida L, Geiger D, Hummel R. Junctions: Detection, classification, and reconstruction[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1998, 20(7): 687-698.
  • 8Schimid C, Mohr R, Bauckhage C. Evaluation of interest point detectors[J]. International Journal of Computer Vision, 2000, 37(2): 151-172.
  • 9Lindeberg T. Scale-space theory: A basic tool for analysing structures at different scales[J]. Journal Applied Statistics, 1994, 21(2): 223-261.
  • 10Babaud J, Witkin A P, Baudin M, et al. Uniqueness of the Gaussian kernel for scale-space filtering[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1986, 8(1): 26-33

共引文献85

同被引文献21

  • 1肖阳辉,张帆.一种改进的红外图像角点检测算法[J].仪器仪表学报,2006,27(z3):2237-2239. 被引量：2
  • 2马苗,张艳宁,赵健,灰色理论及其在图像工程中的应用[M].北京:清华大学出版社,2011.
  • 3ALBERT F,PACHECO D G,ALEIXOS N. New methodto find corner and tangent vertices in sketches using para-metric cubic curves approximation [J]. Pattern Recogni-tion, 2013,46: 1433-1448.
  • 4CHEN L,LU W, NI J, et al. Region duplication detec-tion based on Harris comer points and step sector statis-tics [J]. Journal of Visual Communication and ImageRepresentation, 2013 , 24(3) : 244-254.
  • 5HARRIS C, STEPHENS M. A combined comer and edgedetector [C]. Alvey Vision Conference, 1988, 15:147-151.
  • 6SMITH S M, BRADY J M. SUSAN—A new approach tolow level image processing [J]. International journal ofcomputer vision, 1997,23(1) ; 45-78.
  • 7GUEGUEN L, PESARESI M. Multi scale Harris comerdetector based on differential morphological decomposi-tion [J]. Pattern Recognition Letters, 2011,32(14):1714-1719.
  • 8LUGUANG C, HUIQING Z. An adaptive global motionestimation method based on improved SUSAN algorithmand SIFT algorithm [C]. IEEE Control and DecisionConference (CCDC),2013: 2815-2819.
  • 9JEON B S,WOO D G, MO Y H, et al. An improvedcomer point detection using extreme value of Susan meth-od for measuring a displacement [C]. IEEE,ICCAS-SICE, 2009: 5392-5396.
  • 10LI H, GUO L,CHEN T,et al. The comer detector ofteeth image based on the improved SUSAN algorithm[C].IEEE International Conference on Biomedical Engineeringand Informatics, 2010,2: 609-612.

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