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Three-Dimensional Shape Analysis Using Moments and Fourier Descriptors
November 1988 (vol. 10 no. 6)
pp. 937-943

A procedure for using moment-based feature vectors to identify a three-dimensional object from a two-dimensional image recorded at an arbitrary viewing angle and range is presented. A moment form called standard moments, rather than the usual moment invariants, is considered. A standard six-airplane experiment was used to compare different techniques. Fourier descriptors and moment invariants were both compared to the present scheme for normalized moments. Various experiments were conducted using mixtures of silhouette and boundary moments and different normalization techniques. Standard moments gave slightly better results than Fourier descriptors for this experiment; both of these techniques were much better than moment invariants.

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Index Terms:
3-D shape analysis; pattern recognition; 2-D image; picture processing; Fourier descriptors; silhouette; boundary moments; Fourier analysis; pattern recognition; picture processing
Citation:
A.P. Reeves, R.J. Prokop, S.E. Andrews, F.P. Kuhl, "Three-Dimensional Shape Analysis Using Moments and Fourier Descriptors," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 10, no. 6, pp. 937-943, Nov. 1988, doi:10.1109/34.9115
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