A maximum likelihood estimation (MLE) method is used to estimate the fractal dimension of a number of natural texture images with and without the presence of noise. An additional texture measure which can be linked to...
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A maximum likelihood estimation (MLE) method is used to estimate the fractal dimension of a number of natural texture images with and without the presence of noise. An additional texture measure which can be linked to the lacunarity measure is used to characterize natural textures since fractal dimension alone cannot totally characterize texture images. Segmentation of natural textures is successfully achieved by a k-means clustering algorithm using fractal dimension and the additional measure as representative features.< >
Edge-based image segmentation is a two-stage process;edge enhancement followed by edge linking. Modern approaches for edge enhancement use either the gradient of the Gaussian operator (VG) or the Laplacian of the Gaus...
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The medial axis transform (MAT) is a sparse representation of shape, which, being reversible, has potential for binary image compression. The MAT also provides structural information not accessible with alternative bi...
Generic shape recognition is the problem of determining the pose and dimensions of objects for which only shape models are available and the object's size is unknown. One application domain for generic object reco...
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Generic shape recognition is the problem of determining the pose and dimensions of objects for which only shape models are available and the object's size is unknown. One application domain for generic object reco...
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Generic shape recognition is the problem of determining the pose and dimensions of objects for which only shape models are available and the object's size is unknown. One application domain for generic object recognition is the handling and sorting of postal objects. Because metrical information relating object features to one another is not available, the more common feature-based approaches are inadequate. INGEN (inference engine for generic object recognition), uses a data-driven approach to determine the pose and size of objects with generic shapes such as parallelepipeds and cylinders. This system successfully recognizes occluded objects in heaps. It also handles scenes which have irregularities in surfaces and edges-such irregularities are common to postal objects-as well as shadows and irregularities in the range data itself.< >
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