An Enhanced Detector of Blurred and Noisy Edges

Detecting edges in digital images is a tricky operation in image processing since images may contain areas with different degrees of noise, blurring and sharpness. Such operation represents an important step of the whole process of similarity shape analysis and retrieval.

[1]  Zhengwei Yang,et al.  Invariant matching and identification of curves using B-splines curve representation , 1995, IEEE Trans. Image Process..

[2]  Frédéric Truchetet,et al.  Generalization of Canny-Deriche filter for detection of noisy exponential edge , 2002, Signal Process..

[3]  C.-C. Jay Kuo,et al.  Wavelet descriptor of planar curves: theory and applications , 1996, IEEE Trans. Image Process..

[4]  Pierre Gouton,et al.  Ridge-line optimal detector , 2000 .

[5]  Anuj Srivastava,et al.  Statistical shape analysis: clustering, learning, and testing , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[6]  Rachid Deriche,et al.  Using Canny's criteria to derive a recursively implemented optimal edge detector , 1987, International Journal of Computer Vision.

[7]  Thomas S. Huang,et al.  Image processing , 1971 .

[8]  Dana H. Ballard,et al.  Computer Vision , 1982 .

[9]  Didier Demigny,et al.  On optimal linear filtering for edge detection , 2002, IEEE Trans. Image Process..

[10]  John F. Canny,et al.  A Computational Approach to Edge Detection , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[11]  Lawrence G. Roberts,et al.  Machine Perception of Three-Dimensional Solids , 1963, Outstanding Dissertations in the Computer Sciences.

[12]  D Marr,et al.  Theory of edge detection , 1979, Proceedings of the Royal Society of London. Series B. Biological Sciences.

[13]  Ralph Roskies,et al.  Fourier Descriptors for Plane Closed Curves , 1972, IEEE Transactions on Computers.

[14]  Stéphane Mallat,et al.  Characterization of Signals from Multiscale Edges , 2011, IEEE Trans. Pattern Anal. Mach. Intell..