Detection and thresholding using a stochastic approach is discussed. A general form of detectors which includes a number of well-known detectors as special cases is discussed. Thresholding is indispensable to eliminat...
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ISBN:
(纸本)0818621486
Detection and thresholding using a stochastic approach is discussed. A general form of detectors which includes a number of well-known detectors as special cases is discussed. Thresholding is indispensable to eliminate spurious responses from the detection process. The authors propose a weighted thresholding, which is designed to cope with a variety of anomalies. The analysis and experimental results on real images show that intelligent thresholding methods can make a significant difference for discontinuity detection.
The authors present a physically based approach, using polarization, to distinguish three types of image edges: limb edges, specular edges, and albedo/physical edges. Assuming general imaging conditions and smooth die...
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ISBN:
(纸本)0818621486
The authors present a physically based approach, using polarization, to distinguish three types of image edges: limb edges, specular edges, and albedo/physical edges. Assuming general imaging conditions and smooth dielectric surfaces, a labeling scheme which enables one to distinguish among these edge types has been developed. The method is demonstrated on laboratory images.
The author proposes a junction detector that works by filling in gaps at junctions in edge maps. It uses the image gradient to guide extensions of disconnected edges at junctions. A novel representation for the gradie...
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ISBN:
(纸本)0818621486
The author proposes a junction detector that works by filling in gaps at junctions in edge maps. It uses the image gradient to guide extensions of disconnected edges at junctions. A novel representation for the gradient, the bow tie map, is used to implement the endpoint growing rules, which include following gradient ridges and using saddle points in the gradient magnitude. The authors demonstrate the junction detector on real imagery.
An algorithm is described which performs curvilinear grouping of image edge elements for detecting object boundaries. The method works by generating hypotheses and selecting the best one. A neighborhood definition bas...
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ISBN:
(纸本)0818621486
An algorithm is described which performs curvilinear grouping of image edge elements for detecting object boundaries. The method works by generating hypotheses and selecting the best one. A neighborhood definition based on Delaunay graph is used to keep the number of generated hypotheses small. An energy minimizing curve is fit to the generated hypotheses to evaluate the grouping and locate discontinuities.
The relationship between the skeleton and the Voronoi diagram for the case of morphologically regular sets is described. Using the discrete-point Voronoi diagram, a practical algorithm is developed to compute an appro...
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ISBN:
(纸本)0818621486
The relationship between the skeleton and the Voronoi diagram for the case of morphologically regular sets is described. Using the discrete-point Voronoi diagram, a practical algorithm is developed to compute an approximate skeleton of a continuous shape from sampled data. The analysis also yields a sampling criterion under which the approximation is stable. The algorithm is applied to a simple test image.
A methodology for classifying syntactic patterns that performs a branch-and-bound search over a set of prototypes is proposed. The prototypes are first clustered hierarchically and the search is performed over the hie...
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ISBN:
(纸本)0818621486
A methodology for classifying syntactic patterns that performs a branch-and-bound search over a set of prototypes is proposed. The prototypes are first clustered hierarchically and the search is performed over the hierarchy. The proposed technique is applied to a patternrecognition system in which images are described by the sequence of features extracted from the chain codes of their contours. A rotationally invariant string distance measure is defined that compares two feature strings. The methodology discussed is compared to a nearest neighbor classifier that uses 12,000 prototypes. The proposed technique decreases the time required to recognize a pattern by 93% and maintains a recognition rate of greater than 90%.
Gradient methods are widely used in the computation of optical flow. The authors discuss extensions of these methods which compute probability distributions of optical flow. The use of distributions allows representat...
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ISBN:
(纸本)0818621486
Gradient methods are widely used in the computation of optical flow. The authors discuss extensions of these methods which compute probability distributions of optical flow. The use of distributions allows representation of the uncertainties inherent in the optical flow computation, facilitating the combination with information from other sources. Distributed optical flow for a synthetic image sequence is computed, and it is demonstrated that the probabilistic model accounts for the errors in the flow estimates. The distributed optical flow for a real image sequence is computed.
It is shown that the hitherto heuristic hysteresis linking idea of J. F. Canny (1986) can be formulated as a Bayesian contextual decision process. This approach draws on an explicit image model which accounts both for...
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ISBN:
(纸本)0818621486
It is shown that the hitherto heuristic hysteresis linking idea of J. F. Canny (1986) can be formulated as a Bayesian contextual decision process. This approach draws on an explicit image model which accounts both for the way in which noisy raw-edge information is characterized via filtering operations and how the required edge-connectivity information is quantified. The main advantage is that the previously ad hoc hysteresis thresholds can be related to the parameters of an image model. One feature is the requirement of a third hysteresis threshold based on the consistency of non-edge configurations;this results in an increased capability to reject inconsistent edge candidates. The parameters of the image model can be robustly estimated from image-statistics. The approach endows the hysteresis linking algorithm with adaptive capabilities.
A model-based recognition method that runs in time proportional to the actual number of instances of a model that are found in an image is presented. The key idea is to filter out many of the possible matches without ...
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ISBN:
(纸本)0818621486
A model-based recognition method that runs in time proportional to the actual number of instances of a model that are found in an image is presented. The key idea is to filter out many of the possible matches without having to explicity consider each one. This contrasts with the hypothesize-and-test paradigm, commonly used in model-based recognition, where each possible match is tested and either accepted or rejected. For most recognition problems the number of possible matches is very large, whereas the number of actual matches is quite small, making output-sensitive methods such as this one very attractive. The method is based on an affine invariant representation of an object that uses distance ratios defined by quadruples of feature points. A central property of this representation is that it can be recovered from an image using only pairs of feature points.
Ellipses seen in an image may be the 2-D projection of 3-D circles from the scene. Given this assumption, ellipses can be grouped into perceptual groups from which inferences about the 3-D structure of objects can be ...
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ISBN:
(纸本)0818621486
Ellipses seen in an image may be the 2-D projection of 3-D circles from the scene. Given this assumption, ellipses can be grouped into perceptual groups from which inferences about the 3-D structure of objects can be made. Methods are proposed for extracting groupings corresponding to surfaces of revolution. A Hough transform approach is used for grouping, after which the confidence in the plausibility of the perceptual group is improved by detecting symmetry groupings.
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