Image registration and object recognition using affine invariants and convex hulls

This paper is concerned with the problem of feature point registration and scene recognition from images under weak perspective transformations which are well approximated by affine transformations, and under possible occlusi on and/or appearance of new objects, It presents a set of local absolute af fine invariants derived from the convex hull of scattered feature points (e .g., fiducial or marking points, corner points, inflection points, etc.) ex tracted from the image. The affine invariants are constructed from the area s of the triangles formed by connecting three vertices among a set of four consecutive vertices (quadruplets) of the convex hull, and hence do make di rect use of the area invariance property associated with the affine transfo rmation. Because they are locally constructed, they are very well suited to handle the occlusion and/or appearance of new objects. These invariants ar e used to establish the correspondences between the convex hull vertices of a test image with a reference image in order to undo the affine transforma tion between them, A point matching approach for recognition follows this, The time complexity for registering L feature points on the test image with N feature points of the reference image is of order O(N x L), The method h as been tested on real indoor and outdoor images and performs well.