The Canny detector with edge region focusing using an anisotropic diffusion process

被引:14
作者
Galvanin E.A.S. [1 ]
Do Vale G.M. [1 ]
Dal Poz A.P. [1 ]
机构
[1] São Paulo State University, Department of Cartography, S. Paolo, 19060-900
基金
巴西圣保罗研究基金会;
关键词
Edge Detection; Anisotropic Diffusion; Coarse Scale; Edge Region; Edge Structure;
D O I
10.1134/S1054661806040067
中图分类号
学科分类号
摘要
This paper proposes a methodology for edge detection in digital images using the Canny detector, but associated with a priori edge structure focusing by a nonlinear anisotropic diffusion via the partial differential equation (PDE). This strategy aims at minimizing the effect of the well-known duality of the Canny detector, under which is not possible to simultaneously enhance the insensitivity to image noise and the localization precision of detected edges. The process of anisotropic diffusion via thePDE is used to a priori focus the edge structure due to its notable characteristic in selectively smoothing the image, leaving the homogeneous regions strongly smoothed and mainly preserving the physical edges, i.e., those that are actually related to objects presented in the image. The solution for the mentioned duality consists in applying the Canny detector to a fine gaussian scale but only along the edge regions focused by the process of anisotropic diffusion via the PDE. The results have shown that the method is appropriate for applications involving automatic feature extraction, since it allowed the high-precision localization of thinned edges, which are usually related to objects present in the image. © Nauka/Interperiodica 2006.
引用
收藏
页码:614 / 621
页数:7
相关论文
共 8 条
[1]  
Barcelos C.A.Z., Boaventura M., Silva Jr. E.C., Well-balanced flow equation for noise removal and edge detection, IEEE Trans. Image Processing, (2002)
[2]  
Canny J., A computational approach to edge detection, IEEE Transactions on Pattern Analysis and Machine Intelligence, 8, 6, pp. 679-698, (1986)
[3]  
Dal Poz A.P., Vale G.M., Zanin R.B., Automated road segment extraction by grouping road objects, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2004, 34, pp. 436-439
[4]  
Jain R., Kasturi R., Schunck B.G., Machine Vision, (1995)
[5]  
Nordstrom K.N., Biased anisotropic diffusion: A unified regularization and diffusion approach to edge detection, Image and Vision Computing, 8, pp. 318-327, (1990)
[6]  
Parker J.R., Algorithms for Image Processing and Computer Vision, (1997)
[7]  
Perona P., Malik J., Scale space and edge detection using anisotropic diffusion, IEEE Transactions on Pattern Analysis and Machine Intelligence, 12, 7, pp. 629-639, (1990)
[8]  
Shen J., Castan S., An optimal linear operator for step edge detection, Graphical Models and Image Processing, 54, 2, (1992)