Beginning studies are described aimed at defining a set of features to be used with the Spatial Gray Level Dependence Method (SGLDM) which will measure image characteristics believed to be used by humans in the discri...
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Beginning studies are described aimed at defining a set of features to be used with the Spatial Gray Level Dependence Method (SGLDM) which will measure image characteristics believed to be used by humans in the discrimination of textures. In particular a procedure is described which will allow the SGLDM to be used to measure the unit cell size of textures and the coarseness of textures.
An efficient procedure which integrates feature selection and binary decision tree construction is presented. The nonparametric approach is based on the Kolmogorov-Smirnov criterion which yields an optimal classificat...
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An efficient procedure which integrates feature selection and binary decision tree construction is presented. The nonparametric approach is based on the Kolmogorov-Smirnov criterion which yields an optimal classification decision at each node. By combining the feature selection with the design of the classifier, only the most informative features are retained for classification.
Quantitative analysis of lung tissue micrographs aims primarily at the determination of three-dimensional properties of the lung from two-dimensional micrographs. A computer-based approach to the determination of lung...
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Quantitative analysis of lung tissue micrographs aims primarily at the determination of three-dimensional properties of the lung from two-dimensional micrographs. A computer-based approach to the determination of lung tissue boundaries and triple points and end points from the micrograph is presented. The lung tissue boundaries are determined by histogram enhancement approach and zoom thresholding technique. The binary picture representing the lung tissue is then undergoing a thinning process to generate its skeleton from which the triple points and end points are automatically determined. The processing.algorithms are developed into a software package implemented on a PDP-11/40 minicomputer.
The focus of this study is to develop an understanding of the state of the art in visual motion perception by intelligent systems. The authors examine diverse theoretical and empirical approaches to visual motion anal...
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The focus of this study is to develop an understanding of the state of the art in visual motion perception by intelligent systems. The authors examine diverse theoretical and empirical approaches to visual motion analysis, perception, and understanding. Emphasis is placed on issues of observed object and image sequence description, representation, and perceptual control strategies. The author introduces two concepts in visual motion perception: motion vantage perspective and object motion coherence.
The objective of computer vision system is to outline the objects in a picture and label them with an appropriate interpretation. The system consists of three different types of units, two of which are associative dat...
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The objective of computer vision system is to outline the objects in a picture and label them with an appropriate interpretation. The system consists of three different types of units, two of which are associative data memories implemented as relational databases. The short term memory (STM) contains the raw color picture data and the most current interpretations and deductions about the original scene. The long term memory (LTM) contains a detailed model of the scene under consideration. Results obtained with this system are presented.
This study deals with an optimization technique applied to the problem of stochastic labeling. The authors propose a definition of a global criterion on a set of objects to be labeled that combines both ambiguity and ...
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This study deals with an optimization technique applied to the problem of stochastic labeling. The authors propose a definition of a global criterion on a set of objects to be labeled that combines both ambiguity and consistency with adjustable weights. A projected gradient algorithm is developed to minimize the criterion. Results are shown on a toy example and on the edge detection problem. Comparisons are made with relaxation labeling techniques.
This study presents a suboptimal boundary estimation algorithm for noisy images which is based upon an optimal maximum likelihood problem formulation. Both the maximum likelihood formulation and the resulting algorith...
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This study presents a suboptimal boundary estimation algorithm for noisy images which is based upon an optimal maximum likelihood problem formulation. Both the maximum likelihood formulation and the resulting algorithm are described in detail, and computational results are given. In addition, the potential power of the likelihood formulation is demonstrated through the presentation of three simple but insightful analyses of algorithm performance.
A digital imageprocessing.computer called TEXAC (for its sophisticated ″texture analysis″ capabilities) is the most advanced patternrecognitioncomputer in operation for the processing.of biomedical images. Among ...
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A digital imageprocessing.computer called TEXAC (for its sophisticated ″texture analysis″ capabilities) is the most advanced patternrecognitioncomputer in operation for the processing.of biomedical images. Among the important applications of the instrument is its ability to enhance significantly the image quality of radiograms, and thus to bring out important elements which might otherwise escape detection during a traditional viewbox examination of the original films. TEXAC employs a conventional TV camera to input the x-ray picture. By means of a special algorithm TEXAC completes edge enhancement operations on the x-ray image in a matter of seconds.
It is proposed that the curves commonly encountered in picture processing.can be described by a sequence of arcs linked at critical points. A statistical model is developed which assumes that the locations of the crit...
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It is proposed that the curves commonly encountered in picture processing.can be described by a sequence of arcs linked at critical points. A statistical model is developed which assumes that the locations of the critical points are statistically independent. The model is used to develop and analyze algorithms for determining such critical points.
The problem of texture discrimination is considered. Random walks are performed in a plane domain D bounded by an absorbing boundary GAMMA , and the absorption distribution is calculated. Measurements derived from suc...
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The problem of texture discrimination is considered. Random walks are performed in a plane domain D bounded by an absorbing boundary GAMMA , and the absorption distribution is calculated. Measurements derived from such distributions are the features used for discrimination. Experiments using the model are performed and results are shown.
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