Shape Description and Classification using the Interrelationship of Structures at Multiple Scales

This paper deals with the classification of objects described by planar curves in an image. Invariance to deformation is an important aspect of shape representation and two representations are described with different degrees of such invariance. One of these is a new statistical method for shape description exhibiting a large degree of such invariance. Using scale-space to describe shape statistically allows for a texture-like form of object classification. The scale-space used is one based on curvature-tuned smoothing (CTS). This allows a curve to be represented as a set of descriptors at various scales. The spatial correlation of these descriptors produces a statistical description of a contour that has similarities to a large-scale texture measure. The texture being measured is, in fact, the combination of substructures that define the object’s shape.