The maxima of Curvature Scale Space (CSS) image have been used to represent
2D shapes under affine transforms. The CSS image is expected to be in the
MPEG-7 package of standards, Since th CSS image employs the are length para
metrisation which is not affine invariant, we expect some deviations in the
maxima of the CSS image under general affine transforms. Affine length and
affine curvature have already been introduced and used as alternatives to
are length and conventional curvature in affine transformed environments. T
he utility of using these parameters to enrich the CSS representation is ad
dressed in this payer. We use are length to parametrise the curve Frier to
computing its CSS image. The parametrisation has been proven to be invarian
t under affine transformation and has been used in many affine invariant sh
ape recognition methods. Since the organisation of the CSS image is based o
n curvature zero crossings oi the curve, in this paper, we also investigate
the advantages and shortcomings of using affine curvature in computation o
f the CSS image. The enriched CSS representations are then used to find sim
ilar shapes from a very Large prototype database, and also a small classifi
ed database, both consisting of original as well as affine transformed shap
es. An improvement is observed over the conventional CSS image.