Parameter estimation and reconstruction of digital conics in normal positions

Abstract Reconstruction of the original curve (and the estimation of its parameters) from its digitization is a challenging problem as quantization always causes some loss of information. So we often estimate at least one (or all ) continuous curve(s) which is (are) isomorphic to the original one under discretization. Some work has already been done in this respect on straight lines, circles, squares, etc. In this paper, we have attempted this problem for a specialized class of conics which are said to be in normal positions. In normal position the center of the conic is situated at a grid point and its axes are parallel to the coordinate axes. For circles and parabolas, we can directly formulate the domain, i.e., the entire set of continuous curves which produces the same digitization. For ellipses (and this can be extended to hyperbolas too), we first compute the smallest rectangle containing the domain of the given digitization and then estimate the domain itself. The major contribution of this paper lies in the development of a new method of analysis (via the iterative refinement of parameter bounds) which can be easily extended to other 1- or 2-parameter piecewise monotonic shapes such as straight lines or circles with known radius.

[1]  Akira Nakamura,et al.  Digital images of geometric pictures , 1985, Comput. Vis. Graph. Image Process..

[2]  Samiran Chattopadhyay,et al.  A new method of analysis for discrete straight lines , 1991, Pattern Recognit. Lett..

[3]  Chul E. Kim,et al.  Digital Convexity, Straightness, and Convex Polygons , 1982, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[4]  F. Groen,et al.  Freeman-code probabilities of object boundary quantized contours , 1978 .

[5]  Arnold W. M. Smeulders,et al.  Discrete Representation of Straight Lines , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[6]  Arnold W. M. Smeulders,et al.  Best Linear Unbiased Estimators for Properties of Digitized Straight Lines , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[7]  A. Smeulders,et al.  Discrete straight line segments: parameters, primitives and properties , 1991 .

[8]  Chul E. Kim,et al.  Digital Disks , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[9]  Arnold W. M. Smeulders,et al.  Length estimators for digitized contours , 1987, Comput. Vis. Graph. Image Process..