Edge detection: Difference between revisions

Revision as of 19:14, 18 February 2025

Revision as of 19:02, 16 April 2025

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:<math>\theta = \operatorname{atan2}(L_y, L_x).</math>

Other first-order difference operators for estimating image gradient have been proposed in the [[Prewitt operator]], [[Roberts cross]], Kayyali<ref>{{Cite journal|last1=Dim|first1=Jules R.|last2=Takamura|first2=Tamio|date=2013-12-11|title=Alternative Approach for Satellite Cloud Classification: Edge Gradient Application|journal=Advances in Meteorology|language=en|volume=2013|issue=1 |pages=1–8|doi=10.1155/2013/584816|issn=1687-9309|doi-access=free|bibcode=2013AdMet201384816D }}</ref> operator and [[Frei–Chen operator]].

It is possible to extend filters dimension to avoid the issue of recognizing edge in low [[Signal-to-noise ratio|SNR]] image. The cost of this operation is loss in terms of resolution. Examples are Extended Prewitt 7×7.

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=== Connectivity of gradients without using (high) magnitude thresholds ===

This method finds connected set of pixels having a directional derivative magnitude larger than a fairly small threshold.<ref>{{Cite journal |lastlast1=Pak |firstfirst1=Mesut |last2=Bayazit |first2=Ulug |date=2020-07-01 |title=Regional bit allocation with visual attention and distortion sensitivity |url=https://link.springer.com/article/10.1007/s11042-020-08686-z |journal=Multimedia Tools and Applications |language=en |volume=79 |issue=27 |pages=19239–19263 |doi=10.1007/s11042-020-08686-z |issn=1573-7721}}</ref> It considers only presence of gradients instead of strength of gradients. After applying a dramatically small threshold (i.e. 5), a binary image is obtained. The morphological opening operation and the morphological closing operation are applied to the binary image to close gaps. Then, the distance transform operation is applied to the binary image to clear the pixels far from the background, so blob-like shapes or other false labeled regions are deleted from the edge map.

=== Edge thinning ===