A robust edge-detection algorithm which performs equally under a wide variety of noisy situations and a broad range of edges is described. The algorithm is executed in three phases. In phase 1, the step and linear edg...
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ISBN:
(纸本)081861952x
A robust edge-detection algorithm which performs equally under a wide variety of noisy situations and a broad range of edges is described. The algorithm is executed in three phases. In phase 1, the step and linear edges are detected from the noise-corrupted image using a statistical classification technique. In phase 2, all the thin-line edges (i.e., which are lines less than two pixels wide) are detected by a supplementary technique since these edges cannot be detected simultaneously with the other step and linear edges. In phase 3, the spurious edge elements are suppressed and the isolated missing edge elements are interpolated using a number of hypothesized edge-segments. Finally some experimental results are provided to illustrate the success of the algorithm.
Stereo matching is the process of determining correspondences between entities in related images. Often, this is treated as two quite independent subprocesses, namely, segmentation, followed by matching. These process...
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ISBN:
(纸本)081861952x
Stereo matching is the process of determining correspondences between entities in related images. Often, this is treated as two quite independent subprocesses, namely, segmentation, followed by matching. These processes are treated as naturally related, in that partial matching is fed back to the segmentation and both proceed simultaneously in a cooperative fashion. Regions are considered as the primitives to be matched, since many of the shortcomings inherent in approaches based on points or lines can be overcome by taking more developed entities. The implementation is based on maintaining a hierarchy of segmented regions in each image, corresponding to analysis at differing scales. The selection of a particular segmentation in each image at a scale appropriate to each region is validated with reference to the optimal matching region in the other image. Examples of these methods, applied to a synthetic image (incorporating color) and to natural office scenes, are presented.
A nonlinear least-squares optimization technique is proposed which uses the Levenberg-Marquardt method and estimates the motion and structure parameters to a global scale factor by minimizing an objective function. Th...
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ISBN:
(纸本)081861952x
A nonlinear least-squares optimization technique is proposed which uses the Levenberg-Marquardt method and estimates the motion and structure parameters to a global scale factor by minimizing an objective function. This objective function is the mean-square difference between the measured coordinates of feature points in the image plane and the coordinates predicted from the current state estimate. In comparison to existing approaches, this technique converges faster and yields better estimates. A recursive version of this algorithm is developed using the block approach. This algorithm is shown to also track eventful motion effectively. The performance of the proposed technique on real image sequences is also presented. Some performance results are indicated to illustrate the efficacy of this approach.
A novel technique for computing intrinsic surface properties is developed. Intrinsic surface properties refer to those properties of a surface which are not affected by the choice of the coordinate system, the positio...
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ISBN:
(纸本)081861952x
A novel technique for computing intrinsic surface properties is developed. Intrinsic surface properties refer to those properties of a surface which are not affected by the choice of the coordinate system, the position of the viewer relative to the surface, and the particular parametric representation used to describe the imaged surface. Since intrinsic properties are characteristics of a surface, they are ideal for the purpose of representation and recognition. The intrinsic properties of interest here are the principal curvatures, the intrinsic distance, and the lines of curvature. The authors adopt a structured lighting sensing configuration where a grid pattern is projected to encode the object surfaces for analysis. At each stripe junction, the curvature of the projected stripe on the object surface is computed and related to that of the normal section which shares the same tangential direction as the projected curve. The principal curvatures and the their directions at the stripe junction under consideration are then recovered using Euler's theorem.
A Markov random field (MRF) model-based approach to automated image interpretation is described and demonstrated as a region-based scheme. In this approach, an image is first segemented into a collection of disjoint r...
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ISBN:
(纸本)081861952x
A Markov random field (MRF) model-based approach to automated image interpretation is described and demonstrated as a region-based scheme. In this approach, an image is first segemented into a collection of disjoint regions which form the nodes of an adjacency graph. image interpretation is then achieved through assigning object labels, or interpretations, to the segmented regions, or nodes, using domain knowledge, extracted feature measurements, and spatial relationships between the various regions. The interpretation labels are modeled as a MRF on the corresponding adjacency graph, and the image interpretation problem are formulated as a maximum a posteriori (MAP) estimation rule. Simulated annealing is used to find the best realization, or optimal interpretation. Through the MRF model, this approach also provides a systematic method for organizing and representing domain knowledge through the clique functions of the probability density function underlying MRF. Results of image interpretation experiments performed on synthetic and real-world images using this approach are described.
An intermediate representation based on combined edge and surface data is proposed to support the recognition of objects in cluttered scenes. The representation is based don the premise that local structure of surface...
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ISBN:
(纸本)081861952x
An intermediate representation based on combined edge and surface data is proposed to support the recognition of objects in cluttered scenes. The representation is based don the premise that local structure of surface and edge (wings) can be reliably sensed without higher-level models, while global edge, surface, and part structures cannot be. A sensing system for indoor scenes is discussed which allows fusion of an intensity image and an image where depth is coded using structured light. Surface patches are detected and coarsely typed according to only the 2-D structure in the stripped image together with global knowledge of the stripe projection, while edges are detected from intensity gradients or boundaries of stripe patches. A set of rules is given for describing the 3-D structure corresponding to each wing constructed in the intermediate scene representation. An extended set of rules is proposed for partitioning the set of sensed wings into subsets corresponding to solid-object parts. Reasonable results are reported when these rules are applied to several complex scenes.
The authors present the main results of a theory of photometric stereo for non-Lambertian surfaces. First, they propose a class of reflectance maps that can be used for a realistic representation of real-world reflect...
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ISBN:
(纸本)081861952x
The authors present the main results of a theory of photometric stereo for non-Lambertian surfaces. First, they propose a class of reflectance maps that can be used for a realistic representation of real-world reflection. Second, they ask how many light sources are needed for inverting this class of reflectance maps. It is shown that three light sources are sufficient for a globally unique inversion for the entire class of reflectance maps. Finally, the authors address the issue of completeness of reconstruction. They show that if k lights are sufficient for a globally unique inversion, 2k lights are necessary for a complete inversion.
A novel depth computation algorithm is described. Based on linear equations derived from the consideration of relative normal velocity, this algorithm determines depth values locally and uniquely from normal velocitie...
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ISBN:
(纸本)081861952x
A novel depth computation algorithm is described. Based on linear equations derived from the consideration of relative normal velocity, this algorithm determines depth values locally and uniquely from normal velocities. Multiple independently moving objects present no problem for the algorithm. A velocity constraint is implemented to estimate normal velocities from intensity images. Experiments to determine depth values from both synthetic images and real images are presented. The experiments show that the depth-recovery algorithm can recover correct values from intensity images. The accuracy of the depth values depends heavily on the accuracy of the normal velocities.
A two-stage algorithm for visual surface reconstruction while preserving discontinuities is presented. The primary contribution is the second stage, a weighted bicubic spline as a surface descriptor. The weighted bicu...
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ISBN:
(纸本)081861952x
A two-stage algorithm for visual surface reconstruction while preserving discontinuities is presented. The primary contribution is the second stage, a weighted bicubic spline as a surface descriptor. The weighted bicubic spline has a factor in the regularizing term that adapts the behavior of the spline across the discontinuity. The weighted bicubic interpolating spline is able to interpolate data with step discontinuities with no discernible distortion (such as Gibbs phenomena) in the interpolated surface. Since regularization is related to spline approximation, extensions to this work should suggest ideas for solving ill-posed problems in vision. Experiments with weighted bicubic spline interpolation are presented.
The authors present a description framework, motivated by perceptual organization, which consists of representations of the geometrical organizations of intensity discontinuities. The descriptors in this framework are...
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ISBN:
(纸本)081861952x
The authors present a description framework, motivated by perceptual organization, which consists of representations of the geometrical organizations of intensity discontinuities. The descriptors in this framework are called collated features, and are groupings identified by perceptual organization. The processes that operate on the image to obtain these descriptors and the visual processes that utilize them are discussed. The detection of collated features is robust to local problems. The structural information encoded in them aids various visual tasks such as object segmentation, correspondence processes (stereo, motion, and model matching), and shape inferences. Two primary grouping processes, cocurvilinearity and symmetry are applied to intensity edge contours to generate the collated features, including curves, symmetries, and ribbons. These collations can be used to segment into visible surfaces of objects and to describe the 2-D shapes of those surfaces.
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