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Surface Reconstruction is the most potent aspect of 3D computer vision. It allows recapturing or imitating of the shape of real objects. It also provides sufficient knowledge regarding the mathematical foundation for rendering applications which are widely used for analyzing medical volume data, modeling, 3D interior designing, architectural designing. In our paper, we have mentioned various algorithms and approaches for surface reconstruction and their applications. Moreover, we have tried to emphasize the necessity of surface reconstruction for solving image analysis related problem. [ABSTRACT FROM AUTHOR]

In this paper, we propose an arc recognition method based on the number theoretic properties of isothetic covers. A definition of digital circles is given based on the dilation of Euclidean circles with unit squares. We show that a variant of the digital circle is equivalent to the grid centers between the isothetic covers of disks. Number theoretic properties of the isothetic covers of disks are explored and show that the distribution of square numbers can be used to find the run lengths of the isothetic covers. Arc recognition algorithms are developed based on the number theoretic properties. [ABSTRACT FROM AUTHOR]

A novel algorithm to detect circular arcs from a digital image is proposed. The algorithm is based on discrete curvature estimated for the constituent points of digital curve segments, followed by a fast geometric analysis. The curvature information is used in the initial stage to find the potentially circular segments. In the final stage, the circular arcs are merged and maximized in length using the radius and center information of the potentially circular segments. Triplets of longer segments are given higher priorities; doublets and singleton arcs are processed at the end. Detailed experimental results on benchmark datasets demonstrate its efficiency and robustness. [ABSTRACT FROM AUTHOR]