Shape similarity retrieval under affine transform: application to multi-view object representation and recognition

Abstract

The maxima of curvature scale space (CSS) image have already been used to represent 2-D shapes in different applications under similarity transforms. We also consider affine transforms and examine their effect on the representation. Since the CSS image employs the arc length parametrisation which is not affine invariant, we expect some deviation in the maxima of the CSS image under affine transforms. We first examine the arc length deviation and then show that the locations of the maxima of the CSS image do not change dramatically even under large affine transformations. Applying affine transforms to every object boundary of our database of 1100 images, we construct a large database of 5500 boundary contours. The CSS representation is then used to find similar shapes from this prototype database. The results provide substantial evidence of stability of the the CSS image and its contour maxima under affine transformation. Our system for shape-based retrieval from large image databases is then applied to multi-view 3-D object representation and recognition. Our collection of 3-D objects consists of 10 aircraft of different shapes. Each object is modelled using a small number of silhouette contours obtained from different view points (four contours in one experiment and nine contours in another). Three silhouette contours corresponding to random views are separately used as input for each object. Results indicate that robust and efficient 3-D free-form object recognition through multi-view representation can be achieved using the CSS representation.