To get a locally optimum feature set, a feature selection method was presen
ted, which combines divergence with Sequential Forward Selection (SFS). Exp
erimental results prove that wavelet moment invariants are superior to Zern
ike's moment invariants for pattern recognition, especially for classifying
seemingly similar objects with subtle difference.