A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Practical methods of optimization; (2nd ed.)
Practical methods of optimization; (2nd ed.)
IEEE Transactions on Pattern Analysis and Machine Intelligence
Numerical recipes in C: the art of scientific computing
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Pattern Recognition Letters
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A Regularized Solution to Edge Detection
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Implementation Of A Theory Of Edge Detection
Implementation Of A Theory Of Edge Detection
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IEEE Transactions on Pattern Analysis and Machine Intelligence
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IEEE Transactions on Pattern Analysis and Machine Intelligence
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IEEE Transactions on Pattern Analysis and Machine Intelligence
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Journal of Mathematical Imaging and Vision
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IEEE Transactions on Pattern Analysis and Machine Intelligence
Edge detection by scale multiplication in wavelet domain
Pattern Recognition Letters
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ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
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CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
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IEEE Transactions on Pattern Analysis and Machine Intelligence
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IEEE Transactions on Pattern Analysis and Machine Intelligence
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Pattern Recognition
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Proceedings of the Second International Conference on Computational Science, Engineering and Information Technology
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Knowledge-Based Systems
Information Sciences: an International Journal
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The authors suggest a regularization method for determining scales for edge detection adaptively for each site in the image plane. Specifically, they extend the optimal filter concept of T. Poggio et al. (1984) and the scale-space concept of A. Witkin (1983) to an adaptive scale parameter. To avoid an ill-posed feature synthesis problem, the scheme automatically finds optimal scales adaptively for each pixel before detecting final edge maps. The authors introduce an energy function defined as a functional over continuous scale space. Natural constraints for edge detection are incorporated into the energy function. To obtain a set of optimal scales that can minimize the energy function, a parallel relaxation algorithm is introduced. Experiments for synthetic and natural scenes show the advantages of the algorithm. In particular, it is shown that this system can detect both step and diffuse edges while drastically filtering out the random noise.