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1 Author(s)
R. M. Haralick ; Machine Vision International, Ann Arbor, MI 48104.

We present evidence that the Laplacian zero-crossing operator does not use neighborhood information as effectively as the second directional derivative edge operator. We show that the use of a Gaussian smoother with standard deviation 5.0 for the Laplacian of a Gaussian edge operator with a neighborhood size of 50 × 50 both misses and misplaces edges on an aerial image of a mobile home park. Contrary to Grimson and Hildreth's results, our results of the Laplacian edge detector on a noisy test checkerboard image are also not as good as the second directional derivative edge operator. We conclude by discussing a number of open issues on edge operator evaluation.

Published in:

IEEE Transactions on Pattern Analysis and Machine Intelligence  (Volume:PAMI-7 ,  Issue: 1 )