A methodology for optical flow analysis based on cepstral filtering is introduced. The power cepstrum is extended to multiframe analysis. A correlative cepstral technique, cepsCorr, is developed. It significantly incr...
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A methodology for optical flow analysis based on cepstral filtering is introduced. The power cepstrum is extended to multiframe analysis. A correlative cepstral technique, cepsCorr, is developed. It significantly increases the signal-to-noise ratio, reduces ambiguities, and it provides a predictive or multievidence approach to visual motion analysis.< >
Two iterative algorithms for shape reconstruction based on multiple images taken under different lighting conditions, known as photometric stereo, are proposed. It is shown that single-image shape-from-shading (SFS) a...
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Two iterative algorithms for shape reconstruction based on multiple images taken under different lighting conditions, known as photometric stereo, are proposed. It is shown that single-image shape-from-shading (SFS) algorithms have an inherent problem, i.e., the accuracy of the reconstructed surface height is related to the slope of the reflectance map function defined on the gradient space. This observation motivates the authors to generalize the single-image SFS algorithm to two photometric stereo SFS algorithms aiming at more accurate surface reconstruction. The two algorithms directly determine the surface height by minimizing a quadratic cost functional, which is defined to be the square of the brightness error obtained from each individual image in a parallel or cascade manner. The optimal illumination condition that leads to best shape reconstruction is examined.< >
A CAD-model-based machine vision system for dimensional inspection of machine parts is described, with emphasis on the theory behind the system. The original contributions of this work are: (1) the use of precise defi...
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A CAD-model-based machine vision system for dimensional inspection of machine parts is described, with emphasis on the theory behind the system. The original contributions of this work are: (1) the use of precise definitions of geometric tolerances suitable for use in imageprocessing. (2) the development of measurement algorithms corresponding directly to these definitions, (3) the derivation of the uncertainties in the measurement tasks, and (4) the use of this uncertainty information in the decision-making process. Initial experimental results have verified the uncertainty derivations statistically and proved that the error probabilities obtained by propagating uncertainties are lower than those obtainable without uncertainty propagation.< >
The authors describe how to design color illumination to improve the discriminability of objects in color images. This procedure is useful in applications where the illumination can be controlled, such as inspection t...
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The authors describe how to design color illumination to improve the discriminability of objects in color images. This procedure is useful in applications where the illumination can be controlled, such as inspection tasks. From the physics of color image formation, the optimal color illumination for discriminating materials is derived using a parametrically defined set of illuminants. The authors suggest how such an approach might be extended to sets of materials and more general classes of light sources. Experiments with painted color patches and live potato plantlets are used to illustrate the usefulness of actively controlling illumination color in machine vision.< >
A multiscale filtering scheme based on the three Matheron axioms for morphological openings is developed. It is shown that opening a signal with a gray scale operator does not introduce additional zero-crossings as on...
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A multiscale filtering scheme based on the three Matheron axioms for morphological openings is developed. It is shown that opening a signal with a gray scale operator does not introduce additional zero-crossings as one moves to coarser scales. Within this framework, the problem of choosing an appropriate structuring element is studied. In order to obtain a measure of the performance of different structuring elements, the statistical properties of gray scale opening are studied, using a powerful tool in mathematical morphology, namely, basis functions.< >
The history of the image understanding environment (IUE) project, a five-year program to develop a common software environment for the development of algorithms and application systems, is reviewed. An overview of som...
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The history of the image understanding environment (IUE) project, a five-year program to develop a common software environment for the development of algorithms and application systems, is reviewed. An overview of some of the data structures that are currently evolving as a specification for the IUE is provided. The ultimate goal of the project is to provide the basic data structures and algorithms that are required to carry state-of-the-art research in image understanding.< >
The Bayesian segmentation model developed is motivated by consideration of the information needed for higher-level visual processing. A segmentation is regarded as a collection of parameters defining an image-valued s...
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ISBN:
(纸本)0818621486
The Bayesian segmentation model developed is motivated by consideration of the information needed for higher-level visual processing. A segmentation is regarded as a collection of parameters defining an image-valued stochastic process by separating topological (adjacency) and metric (shape) properties of the subdivision and intensity properties of each region. The prior selection is structured accordingly. The novel part of the representation, the subdivision topology, is assigned a prior by universal coding arguments, using the minimum description-length philosophy that the best segmentation allows the most efficient representation of visual data.< >
The extension of the iterated function system (IFS) theory dealing with probability functions instead of numbers is applied to texture analysis. The results allow encoding and reconstruction of textured images, and he...
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ISBN:
(纸本)0818621486
The extension of the iterated function system (IFS) theory dealing with probability functions instead of numbers is applied to texture analysis. The results allow encoding and reconstruction of textured images, and hence the compression of data to tackle the problem of texture segmentation in a rigorous manner.
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.
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