A zero-crossing edge detector with improved localization and robustness to image brightness and contrast manipulations

To characterize edges, this work proposes a zero-crossing detector that attempts to provide a more precise localization of edges together with robustness to brightness and contrast variation in images. Since the algorithm aims to be insensitive to image histogram manipulations, it is based on zero-crossings of the second derivative, and not on first derivative measurements. In order to provide good localization while preserving the true shape of the edges, the detector is based on precise mathematical expressions that represent image derivatives as a vector field, instead of using the Laplacian as a scalar approximation for the image second derivatives. This way, the proposed detector can be viewed as a Marr-Hildreth operator with a more exact mathematical formulation. Finally, to avoid false responses and provide thin edges, some additional checking is performed over the edge candidate points. The method showed good results when compared with well-known edge detectors.