Abstract

A new discrimination method based on fuzzy subset theory is proposed. This approach uses Zernike moment invariants of the silhouette of the unknown object to form a set of fuzzy-weighted quantities called fuzzy quaternions. These are matched against those of known objects at predetermined viewpoints. To speed up the recognition process, a modified simplex version of the Nelder-Mead algorithm is utilised. Results obtained demonstrate the potential of the fuzzy quaternion as a viable basis for discrimination.

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