By means of combining imageprocessing, character recognition and interactive computer graphics techniques a system has been developed for the acquisition of map data which is required by various urban and regional la...
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By means of combining imageprocessing, character recognition and interactive computer graphics techniques a system has been developed for the acquisition of map data which is required by various urban and regional land-use systems. The system is described.
Given a particular encoding scheme, the complexity of a picture may be measured as the length of its encoding. An encoding scheme is described which is based on a hierarchy of resolution levels. The expected complexit...
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Given a particular encoding scheme, the complexity of a picture may be measured as the length of its encoding. An encoding scheme is described which is based on a hierarchy of resolution levels. The expected complexity of random pictures is computed. However, this method has some advantages. Here complexity tends to be more a function of shape than of size or position. Also, any prefix of the encoding string for a picture describes a simplified approximation to the picture. Potential applications are discussed.
An image segmentation technique is proposed which uses a texture measure that counts the number of local extrema in a window centered at each picture point. Four gray level pictures are derived, each of which represen...
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An image segmentation technique is proposed which uses a texture measure that counts the number of local extrema in a window centered at each picture point. Four gray level pictures are derived, each of which represents a texture or gray level property of the original image. These intermediate pictures are used to derive starting points in each region to be segmented. The segmentation is completed by assigning each pixel to a starting point using a distance criteria. This process can be repeated in a hierarchical structure by using diminishing window sizes. Almost real-time video implementation seems feasible.
The objective of this work is to create an algorithm that will generate a table of colors with maximum contrast among the colors. An algorithm for color generation is developed using as parameters the total number of ...
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The objective of this work is to create an algorithm that will generate a table of colors with maximum contrast among the colors. An algorithm for color generation is developed using as parameters the total number of colors to be produced, the number of colors to be grouped for maximum intra-group contrast, the number of saturation levels, and an arbitrary rotation of the selected colors preserving all the other relationships. The Hering opponent color theory restricted to the red-green and blue-yellow dimensions yields a two-dimensional color model which is used as the basis of the color selection process.
Nuclear medicine is a speciality which attempts to measure in-vivo the biochemical and physiological processes of the human body in a non-invasive manner. This paper discusses numerical analysis and pattern recognitio...
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Nuclear medicine is a speciality which attempts to measure in-vivo the biochemical and physiological processes of the human body in a non-invasive manner. This paper discusses numerical analysis and patternrecognition methods in clinical and image research as employed in nuclear medicine.
New and useful results on multistage multiclass statistical classification and on model-driven, data-directed structural pattern analysis have been obtained by developing and exploiting connections between state-space...
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New and useful results on multistage multiclass statistical classification and on model-driven, data-directed structural pattern analysis have been obtained by developing and exploiting connections between state-space and AND/OR graph models, formal grammars, heuristic search and probabilistic decision making. This paper highlights the concepts and connections which have led to these results.
A solution is given to the linear discrimination problem for more than two statistical classes, using a Generalized Fisher Criterion as distance measure. With the use of linear manifold subspace and decomposition of t...
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A solution is given to the linear discrimination problem for more than two statistical classes, using a Generalized Fisher Criterion as distance measure. With the use of linear manifold subspace and decomposition of the optimization problem into a union of simple convex constrained ones, a closed form solution for the optimal X is attained, and no numerical optimization techniques are needed.
This paper discusses a structural patternrecognition methodology which combines some ideas about relation homomorphisms and theory of covers. Features from any arrangement are determined by calculating to which basis...
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This paper discusses a structural patternrecognition methodology which combines some ideas about relation homomorphisms and theory of covers. Features from any arrangement are determined by calculating to which basis arrangements the given arrangement is a homomorphism and calculating which basis arrangements are isomorphic to some part of the given arrangement. A decision rule then decides which class the given arrangement is assigned using the theory of covers. The methodology suggested in the paper provides an alternative to syntactic patternrecognition.
An algorithm to find linear representations of images is developed such that the obtained straight lines are optimal in the Hausdorff metric. This algorithm avoids the computational difficulties associated with direct...
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An algorithm to find linear representations of images is developed such that the obtained straight lines are optimal in the Hausdorff metric. This algorithm avoids the computational difficulties associated with direct application of the definition of the Hausdorff distance between point sets.
An approach to machine recognition and understanding of pictures via textural feature extraction is presented. Gradient distribution matrices are used to obtain numerous textural measurements. Based upon Karhunen-Loev...
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An approach to machine recognition and understanding of pictures via textural feature extraction is presented. Gradient distribution matrices are used to obtain numerous textural measurements. Based upon Karhunen-Loeve expansion and normalization, textural features are extracted by computer from these measurements. The textural features serve as the basis for machine recognition and understanding of pictures.
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