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In this paper we present a new methodology for edge detection in digitalimages. The first originality of the proposed method is to consider imagecontent as a parametric surface. Then, an original parametric local model ofthis surface representing image content is proposed. The few parametersinvolved in the proposed model are shown to be very sensitive todiscontinuities in surface which correspond to edges in image content. Thisnaturally leads to the design of an efficient edge detector. Moreover, athorough analysis of the proposed model also allows us to explain how theseparameters can be used to obtain edge descriptors such as orientations andcurvatures.  In practice, the proposed methodology offers two main advantages. First, ithas high customization possibilities in order to be adjusted to a wide range ofdifferent problems, from coarse to fine scale edge detection. Second, it isvery robust to blurring process and additive noise. Numerical results arepresented to emphasis these properties and to confirm efficiency of theproposed method through a comparative study with other edge detectors.

A new Edge Detector Based on Parametric Surface Model: Regression Surface Descriptor