Given a set of points S ∈ R 2 , reconstruction is a process of identifying the boundary edges that best approximates the set of points. In this paper, we propose a unified algorithm for reconstruction that works for both dot patterns as well as boundary samples. The algorithm starts with computing the Delaunay triangulation of the given point set and edges are iteratively removed based on the structure of a pair of triangles. Further, we also propose additional criteria for removing edges based on characterizing a triangle and using degree constraint. Unlike the existing algorithms, the proposed approach requires only a single pass to capture both inner and outer boundaries irrespective of the number of objects/holes. Moreover, the same criterion has been employed for both inner and outer boundary detection. The experiments show that our approach works well for different kinds of inputs. We have done extensive comparisons with state-of-the-art methods for various kinds of point sets including varying the sampling density and distribution and found to perform better or on par with them.