Weighted least squares method for the approximation of directional derivatives

Using the facet model we design a family of filters for the approximation of partial derivatives of the digital image surface. Prior information (e.g., local dominant orientation) is incorporated in a two-dimensional weight function. A weighted least squares estimation of the facet parameters is applied in order to design the proposed filters. Exemplary application of the proposed filters to fingerprint image segmentation is also presented.