A fuzzy adaptive distance dynamic clusters (FADDC) algorithm, which is specially designed to search for clusters that lie in subspaces (such as lines, and (hyper)planes) is presented. One major drawback of all cluster...
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ISBN:
(纸本)0818621486
A fuzzy adaptive distance dynamic clusters (FADDC) algorithm, which is specially designed to search for clusters that lie in subspaces (such as lines, and (hyper)planes) is presented. One major drawback of all clustering algorithms is that the number of clusters has to be known a priori. A novel compatible cluster merging (CCM) technique, which finds the optimum number of clusters in an efficient way, is proposed. Such subspace clustering techniques may be used for character recognition and to obtain straight-line descriptions of an edge image. They may also be used to obtain planar approximations of 3-D (range) data. The effectiveness of the proposed algorithms in several such situations is demonstrated with real data.
A multidimensional edge model is established and a first-order estimation for multidimensional edge profiles is proposed. An optimal edge location detection algorithm is developed. The advantages of the algorithm are ...
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ISBN:
(纸本)0818621486
A multidimensional edge model is established and a first-order estimation for multidimensional edge profiles is proposed. An optimal edge location detection algorithm is developed. The advantages of the algorithm are that (1) it has little dependence on assumptions of edge models, noise models, or smoothing filters, (2) it has better abilities for detecting very weak edges and making less edge orientation errors than other edge detectors, (3) it can handle corners and complicated multidimensional image structures, and (4) it detects different edge types at the same time.
Rigid 3-D objects were modeled automatically from an image sequence taken by a camera that was rotated around the object. The image sequence was recorded using a calibrated camera which allows one to measure the camer...
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ISBN:
(纸本)0818621486
Rigid 3-D objects were modeled automatically from an image sequence taken by a camera that was rotated around the object. The image sequence was recorded using a calibrated camera which allows one to measure the camera positions and to estimate the true object size. The 3-D object shape was obtained in two steps. The object silhouettes were employed to find the enclosing volume of the object. The volume was converted into a flexible surface representation and the 3-D shape was refined based on the texture information of the object surface. Texture mapping was applied to generate a highly realistic 3-D model of the object.
The surface reconstruction problem is formulated as a two-stage reconstruction procedure. The first stage is a robust local fit to the data in a multiresolution scheme and the second is a regularized least squares fit...
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ISBN:
(纸本)0818621486
The surface reconstruction problem is formulated as a two-stage reconstruction procedure. The first stage is a robust local fit to the data in a multiresolution scheme and the second is a regularized least squares fit with the addition of an adaptive mechanism in the smoothness functional in order to make the solution well behaved. The authors present the details of the second stage in which they use the weighted bicubic spline as a surface representation in a regularization framework, with a Tikhonov stabilizer as the smoothness norm. It is shown how the adaptive weights in the stabilizer help the surface bend across discontinuities by varying the energy of the surface.
A novel approach to incrementally estimating visual motion over a sequence of images is presented. The authors start by formulating constraints on image motion to account for the possibility of multiple motions. This ...
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ISBN:
(纸本)0818621486
A novel approach to incrementally estimating visual motion over a sequence of images is presented. The authors start by formulating constraints on image motion to account for the possibility of multiple motions. This is achieved by exploiting the notions of weak continuity and robust statistics in the formulation of a minimization problem. The resulting objective function is non-convex. Traditional stochastic relaxation techniques for minimizing such functions prove inappropriate for the task. A highly parallel incremental stochastic minimization algorithm is presented which has a number of advantages over previous approaches. The incremental nature of the scheme makes it dynamic and permits the detection of occlusion and disocclusion boundaries.
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.
Two patternrecognition algorithms are proposed to detect two types of knots in lumber, lumped and surface knots, using an optical scanner. It is shown that lumped knots can be recognized by a log profile approach and...
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ISBN:
(纸本)0818621486
Two patternrecognition algorithms are proposed to detect two types of knots in lumber, lumped and surface knots, using an optical scanner. It is shown that lumped knots can be recognized by a log profile approach and surface knots can be detected by an imageprocessing.approach. A mathematical model for describing the geometry of the knots inside the log based on the surface parameters of the knots is presented. By a log breakdown strategy, the log can be cut into a maximum number of boards with prescribed dimensionalities. The mathematical knot model can be used to predict the locations, sizes, orientations, and shapes of the knots on these boards, whereby their lumber grades can be determined. Summing up the value yields of all the boards gives the value yield of the log. By computing all the possible value yields of the log from different log orientations, one can determine a maximum value yield of a log.
In a binocular camera system moving through the environment, it is possible to obtain a three-dimensional field of vectors, where each vector is parallel to the actual inducing 3-D motion of an imaged point (relative ...
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ISBN:
(纸本)0818621486
In a binocular camera system moving through the environment, it is possible to obtain a three-dimensional field of vectors, where each vector is parallel to the actual inducing 3-D motion of an imaged point (relative to the moving camera), and scaled in magnitude by the depth of that point. The authors derive this 3-D vector field (the p-field), discuss its computation from the image quantities of optic flow and disparity, and examine its behavior for specific cases of motion as well as for general motion. They present experimental results in computing this vector field and discuss issues related to the determination of the motion parameters from it. The results are demonstrated on synthetic and real data.
Multichannel filtering techniques are presented for obtaining both region- and edge-based segmentations of textured images. The channels are represented by a bank of even-symmetric Gabor filters that near uniformly co...
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ISBN:
(纸本)0818621486
Multichannel filtering techniques are presented for obtaining both region- and edge-based segmentations of textured images. The channels are represented by a bank of even-symmetric Gabor filters that near uniformly covers the spatial-frequency domain. Feature images are obtained by subjecting each (selected) filtered image to a nonlinear transformation and computing a measure of energy around each pixel. Region-based segmentations are obtained by using a square-error clustering algorithm. Edge-based segmentations are obtained by applying an edge detector to each feature image and combining their magnitude responses. An integrated segmentation technique that combines the strengths of the previous two techniques while eliminating their weaknesses is proposed. The integrated approach is truly unsupervised, since it eliminates the need for knowing the exact number of texture categories in the image.
A curvature-based approach to estimating nonrigid deformation of moving surfaces is described. Conformal motion can characterized by stretching of the surface. At each point this stretching is equal in all directions,...
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ISBN:
(纸本)0818621486
A curvature-based approach to estimating nonrigid deformation of moving surfaces is described. Conformal motion can characterized by stretching of the surface. At each point this stretching is equal in all directions, but is different for different points. This stretching function can be defined as an additional (with global translation and rotation) motion parameter. An algorithm for local stretching recovery from Gaussian curvature based on polynomial approximations of the stretching function is presented. These methods require point correspondences between time frames, but not the complete knowledge of nonrigid transformation.
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