A new application for clustering is introduced. Clustering is used here for region selection in problems such as piecewise linear classification and density estimation. This method may prove fruitful in a wide class o...
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A new application for clustering is introduced. Clustering is used here for region selection in problems such as piecewise linear classification and density estimation. This method may prove fruitful in a wide class of problems in which one needs to divide the probability space into local regions and thus attack the problem at a localized level. Another advantage to this technique is its easy adaptability to a tree structure for region devision. The technique is discussed and results given.
Analysis of the LANDSAT multispectral scanner data undertaken in the context of identification of wheat, reveals that the data from all agricultural sites essentially lie on parallel two-dimensional planes in the four...
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Analysis of the LANDSAT multispectral scanner data undertaken in the context of identification of wheat, reveals that the data from all agricultural sites essentially lie on parallel two-dimensional planes in the four-dimensional feature space; and that even though the spectral response of wheat at each stage of the crop varies considerably from field to field, the pattern of temporal changes in the response is similar for each field. This temporal pattern, then, constitutes a signature of wheat and provides a basis for both supervised and unsupervised classification of data.
Stochastic representation of discrete images by partial differential equations proposed earlier is used for filtering of noisy images. Comparisons among various representations and their relative effectiveness in mode...
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Stochastic representation of discrete images by partial differential equations proposed earlier is used for filtering of noisy images. Comparisons among various representations and their relative effectiveness in modeling the actual statistics of the images is shown by examples. Certain image decompositions resulting in fast filtering algorithms are given. The results are also compared with spatial averaging and Fourier domain Wiener filters.
The problem of finding approximate matches of pieces of shapes to parts of larger shapes is investigated. The shapes are represented by hierarchical polygonal approximations. Initially, figures of merit are assigned t...
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The problem of finding approximate matches of pieces of shapes to parts of larger shapes is investigated. The shapes are represented by hierarchical polygonal approximations. Initially, figures of merit are assigned to the matches between pairs of angles on the two shapes. Relaxation methods are then used to find acceptable combinations of these matches. This approach was tested on a data base consisting of digitized coastlines in various map projections. In nearly all cases, all matches except the correct one were eliminated by the relaxation processes.
This paper reviews recent developments in the use of iterative (or ″relaxation″ ) methods in image analysis. Applications of these methods include histogram modification, noise cleaning, edge and curve detection, th...
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This paper reviews recent developments in the use of iterative (or ″relaxation″ ) methods in image analysis. Applications of these methods include histogram modification, noise cleaning, edge and curve detection, thinning, angle detection, template matching, and region labelling. These applications are briefly described, and references are given to papers and reports in which more detailed discussions and examples can be found.
An algorithm for constructing regions from their list of boundary points is presented. Both adjacency and containment of regions can be handled. The construction is based on a small set of boundary types which determi...
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An algorithm for constructing regions from their list of boundary points is presented. Both adjacency and containment of regions can be handled. The construction is based on a small set of boundary types which determine the labelling of interior points. All regions are processed together so that time and storage requirements are minimized.
An application is presented of symmetric axis geometry to shape classification and description. Shapes are segmented into simplified segments, in which a sequential string of features are derived. These are based on b...
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An application is presented of symmetric axis geometry to shape classification and description. Shapes are segmented into simplified segments, in which a sequential string of features are derived. These are based on both width and axis properties, and two linear combinations of them, as well as their derivatives. A weighting measure is developed which evaluates the importance of these shape descriptors. Consequently, small perturbations are recognizable despite their generation of sizable symmetric axis arcs. A variety of other segment measures for shape are introduced.
A method is suggested for transforming a polygonal object into a binary relation whose clusters represent intuitively pleasing simple parts of the object. The graph theoretic clustering method determines near-cliques,...
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A method is suggested for transforming a polygonal object into a binary relation whose clusters represent intuitively pleasing simple parts of the object. The graph theoretic clustering method determines near-cliques, which are local regions of high compactness, and then forms clusters by merging those near-cliques having high enough overlap. Using this procedure on the shape of a colon as seen in an X-ray, it was found that for many colon examples, the parts determined by the clustering scheme corresponded well to the decomposition a human might make.
A class of error-correcting tree automata is studied. Syntax errors on trees are defined in terms of five transformations - substitution, stretch, split, branch, and deletion. The distance between two trees is defined...
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A class of error-correcting tree automata is studied. Syntax errors on trees are defined in terms of five transformations - substitution, stretch, split, branch, and deletion. The distance between two trees is defined as the minimum cost sequence of error transformations needed to derive one from the other. This definition provides a similarity measure for syntactic patterns. For a given noisy input tree and a free language, the proposed generalized error-correcting tree automaton (GECTA) will produce a tree in the language using the minimum-distance criterion.
Three transformations used in the analysis of tricolor natural scenes are analyzed: saturation, hue, and normalized color. All have nonremovable singularities, near which they are highly unstable. Given digital input,...
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Three transformations used in the analysis of tricolor natural scenes are analyzed: saturation, hue, and normalized color. All have nonremovable singularities, near which they are highly unstable. Given digital input, the distribution of their transformed values is highly nonuniform, characterized by spurious modes and gaps. These effects are quantified and illustrated. image segmentation techniques of edge detection, region growing, clustering, and region splitting are affected arbitrarily badly by such problems. Some stratagems are illustrated that help minimize the bad behavior.
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