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This paper presents a new feature vector for statistical pattern recognition based on the theory of moments, namely the Normalized Complex Moment Components (NCMC). The NCMC will be evaluated in the recognition of objects which share identical silhouettes using grayscale images and its performance will be compared with that of a commonly used moment based feature vector, the Hu moment invariants....
To match multiple views of a 3D scene, their relative geometric distortions have to be taken into account. We assume the disortions can be approximated by affine transformations. Images are matched by combining an exhaustive and directed unconstrained Hooke-Jeeves search for affine parameters, image pyramids being used to accelerate the search. The parameters found for several matches are statistically...
Visual object recognition is a difficult task when we consider non controlled environments. In order to manage problems like scale, viewing point or occlusions, local representations of objects have been proposed in the literature. In this paper, we develop a novel approach to automatically choose which samples are the most discriminant ones among all the possible local windows of a set of objects...
Recognition of occluded objects in synthetic aperture radar (SAR) images is a significant problem for automatic object recognition. Stochastic models provide some attractive features for pattern matching and recognition under partial occlusion and noise. In this paper, we present a hidden Markov modeling (HMM) based approach for recognizing objects in synthetic aperture radar (SAR) images. We identify...
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