A partial-shape-recognition technique utilizing local features described by Fourier descriptors is introduced. A dynamic programming formulation for shape matching is developed, and a method for comparison of match quality is discussed. This technique is shown to recognize unknown contours that may be occluded or that may overlap other objects. Precise scale information is not required, and the unknown objects may appear at any orientation with respect to the camera. The segment-matching dynamic programming method is contrasted with other sequence-comparison techniques that utilize dynamic programming. Experimental results are discussed that indicate that partial contours can be recognized with reasonable accuracy.>

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.>