Abstract
This paper incrementally extends the energy minimization techniques for image analysis developed by [Koch et al. 1986]. Our application is edge extraction and we use the dual intensity and line processes introduced by [Geman and Geman, 1984]. The approach seeks to minimize a global energy functional that explicitly incorporates image properties to be minimized into weighted terms of the energy functional. Our specific contribution is modifying the weighting of terms in the energy functional that were previously independent of spatial gray level change to explicitly include spatial change in the weighting. We argue that the weighting used in previous implementations resulted in a reduced contribution from the edge components due to a dominance of the spatial intensity difference term as that spatial difference increases in size. Our specific modification compensates for this effect by scaling the edge process weighting factors by the spatial difference value (to the second order), thus, maintaining the same relative effect as the spatial difference increases. We found that the proposed algorithm works significantly better as compared to Koch et al. because of this modification.
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© 1997 Springer-Verlag Berlin Heidelberg
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Bhuiyan, M.S., Iwahori, Y., Iwata, A. (1997). Optimal edge detection under difficult imaging conditions. In: Chin, R., Pong, TC. (eds) Computer Vision — ACCV'98. ACCV 1998. Lecture Notes in Computer Science, vol 1352. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-63931-4_194
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DOI: https://doi.org/10.1007/3-540-63931-4_194
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