An approach to feature detection in image approximation networks is presented. The network is an approximation of the image data surface. The extraction of global image features from the network is described. Primitiv...
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An approach to feature detection in image approximation networks is presented. The network is an approximation of the image data surface. The extraction of global image features from the network is described. Primitive features such as peaks and valleys are located, then ridges and valley lines are traced by iteratively exploring neighboring points of detected features. These topographical features provide a region segmentation of the image. The region boundaries represent global charcteristics of the image data.
An examination is made of the fuzzy approach of E. H. Ruspini to the problem of pattern classification. The problem of classification as that of estimating a partition of the data to be classified is presented. An alg...
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An examination is made of the fuzzy approach of E. H. Ruspini to the problem of pattern classification. The problem of classification as that of estimating a partition of the data to be classified is presented. An algorithm is presented for classifying data issued from a Gaussian environment;the fundamental tool of this algorithm is the use of numerical filters for estimating a set of parameters which characterize each class. This algorithm has been applied to the recognition of the components of a mixture of Normal distributions.
Simulation results are presented for motion compensated hybrid transform/DPCM image coders using coefficient-recursive displacement estimation. computer simulations on two typical real-life sequences of frames show th...
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Simulation results are presented for motion compensated hybrid transform/DPCM image coders using coefficient-recursive displacement estimation. computer simulations on two typical real-life sequences of frames show that displacement based (motion compensated) coefficient prediction results in coder bit rates that are 20 to 40 percent lower than conventional interframe transform coders using 'frame difference of coefficients'.
Inference techniques are applied to computing systems to improve the allocation of resources for fault tolerant performance. Using a general model for such systems, the influence of estimation errors for system parame...
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Inference techniques are applied to computing systems to improve the allocation of resources for fault tolerant performance. Using a general model for such systems, the influence of estimation errors for system parameters on the resulting system fault performance is examined. These results are then applied to the problem of error mode testing-finding the underlying error structure of the system. Simulation is used to illustrate the properties discussed.
A new technique is described fast ″scan-along″ computation of piecewise linear approximations of digital curves in 2-space. Our method is derived from earlier work on the theory of minimum-perimeter polygonal approx...
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A new technique is described fast ″scan-along″ computation of piecewise linear approximations of digital curves in 2-space. Our method is derived from earlier work on the theory of minimum-perimeter polygonal approximations of digitized closed curves. It is demonstrated that the specialization of this technique to the cases where the error is measured as a) the largest Hausdorff-Euclidean distance between the approximation and the given digitized curve, and b) the largest vertical distance between the approximation and a corresponding point on the given digitized curve.
A new class of texture features based on the joint occurrences of gray levels at points defined relative to edge maxima are introduced. These features are compared with previous types of cooccurrence-based features, a...
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A new class of texture features based on the joint occurrences of gray levels at points defined relative to edge maxima are introduced. These features are compared with previous types of cooccurrence-based features, and experimental results are presented indicating that the new features should be useful for texture classification. In the second part, three simple methods of extracting texture primitives are compared. It appears that the simplest of these, thresholding at a fixed percentile, yields primitives that are quite effective in texture discrimination.
Fuzzy subset theory is introduced as a counterpart of the statistical approaches for the classification of Giemsa stained human chromosomes. Although the structure of the chromosome is well-defined, the real appearanc...
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Fuzzy subset theory is introduced as a counterpart of the statistical approaches for the classification of Giemsa stained human chromosomes. Although the structure of the chromosome is well-defined, the real appearance and the artisanal features to classify them are ill-defined. An algorithm based on a split and merge procedure, and describing the chromosome profile in a tree structure, is briefly stated. In order to interpret the features assigned to the nodes a hierarchical aggregation operator is applied for the interpretation of chromosomes.
When radar and optical images are examined in detail, it is often found that the most distinguishable features of the two types of images are the shapes of the objects in the scenes. Therefore, edges can be used to ad...
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When radar and optical images are examined in detail, it is often found that the most distinguishable features of the two types of images are the shapes of the objects in the scenes. Therefore, edges can be used to advantages in the recognition and matching of objects. An edge extraction technique was developed and used to extract the salient outlines of objects of interest. This method also removes many of the edges extracted from the background and shadows around the objects.
The adaptive image filtering considered in this study includes a Kalman filter for noisy image enchancement and a generalized likelihood ratio technique to detect and estimate the jumps corresponding to object boundar...
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The adaptive image filtering considered in this study includes a Kalman filter for noisy image enchancement and a generalized likelihood ratio technique to detect and estimate the jumps corresponding to object boundaries. The filter is adjusted when the jump is detected. When the transition matrix of the filter is unknown, it is determined by a method of simultaneous on-line estimation of parameters and states. Both the mathematical analysis and computer results are presented in detail. The procedures involved are highly effective and flexible, and computationally efficient.
A large number of techniques have been proposed to solve the problem of image reconstruction from its projections in the spatial domain which were shown to be special cases of a general quadratic optimization formulat...
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A large number of techniques have been proposed to solve the problem of image reconstruction from its projections in the spatial domain which were shown to be special cases of a general quadratic optimization formulation. In this study, the problem is formulated as a quadratic optimization in the Fourier domain. Different special cases and interpretations are included. Advantages of such a formulation are discussed, reconstruction algorithms for a separate optimization of magnitude and phase are derived, and finally, computer simulated results are presented.
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