Issue No. 05 - May (1992 vol. 14)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/34.134062
<p>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.</p>
adaptive scale determination; filter scales; edge detection; regularization method; optimal filter; adaptive scale parameter; energy function; continuous scale space; parallel relaxation algorithm; filtering and prediction theory; pattern recognition; picture processing
H. Jeong and C. Kim, "Adaptive Determination of Filter Scales for Edge Detection," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 14, no. , pp. 579-585, 1992.