Invariant feature set in convex hull for fast image registration

In this paper, a novel feature set in images for registration is identified. Unique, geometrically invariant and easily extractable features in images called convex diagonal, convex quadrilateral are used for accurate image registration. Convex diagonals, convex quadrilaterals have attractive properties like easy extraction, geometric invariance and frequent occurrence. Coordinates, length and orientation information of corresponding convex diagonals in different images is used for initial transformation estimate. Corresponding convex hulls of scene objects are matched using Hausdorff distance as similarity measure operator. Coarse level estimate facilitates efficient, real time computation for final registration process. Initial transformation estimate based on convex diagonals, extracted from convex hull of scene objects, is refined using fine level image details to minimize errors originating from quantization and same convex hull information for different object shapes. The behavior of reference quadrilateral is robust against noise, outliers and broken edges.