Affine-invariant curve normalization for object shape representation, classification, and retrieval

• Published in: Machine vision and applications Vol. 13; no. 2; pp. 80 - 94
• Main Authors: Avrithis, Yannis, Xirouhakis, Yiannis, Kollias, Stefanos
• Format: Journal Article
• Language: English
• Published: 01.11.2001
• ISSN: 0932-8092
• DOI: 10.1007/PL00013272

A novel method for two-dimensional curve normalization with respect to affine transformations is presented in this paper, which allows an affine-invariant curve representation to be obtained without any actual loss of information on the original curve. It can be applied as a preprocessing step to any shape representation, classification, recognition, or retrieval technique, since it effectively decouples the problem of affine-invariant description from feature extraction and pattern matching. Curves estimated from object contours are first modeled by cubic B-splines and then normalized in several steps in order to eliminate translation, scaling, skew, starting point, rotation, and reflection transformations, based on a combination of curve features including moments and Fourier descriptors.