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检索条件"任意字段=Intelligent Robots and Computer Vision X: Algorithms and Techniques"

共 1079 条记录，以下是921-930 订阅

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ExTRACTING A SYMBOLIC OBJECT DESCRIPTION FROM GRAY-LEVEL IMAGES USING A KALMAN-FILTER-BASED CONTOUR TRACER COMBINED WITH A COMPLEx EDGE-OPERATOR

EXTRACTING A SYMBOLIC OBJECT DESCRIPTION FROM GRAY-LEVEL IMA...

引用

11TH CONF ON intelligent robots AND computer vision : algorithms, techniques, AND ACTIVE vision

作者： BECKER, M LEY, D Univ. Siegen (Germany)

ISBN: (纸本)0819410268

Usually, gray-level images are arranged as two-dimensional (NxM)-matrices. Tracing its contours is a common way to obtain information about an imaged object, such as position and orientation, or for purposes of object recognition. This paper describes the generation of contour-based object descriptions by edge-detection and contour-tracing. A complex differential operator is used to detect edges in the image. In addition to the gradient, also the local orientation of edges can be computed with an accuracy of approximately 5 degree(s). This edge-oriented description, which is still arranged as a two-dimensional matrix, occupies twice as much memory as the original gray-level image (gradient plus orientation) and there is no knowledge about the course of the contour. In addition to that, in most cases this edge-oriented image is fragmentary, due to illumination restrictions and shades. For this reason the imaged contour is traced using a Kalman-filter-based algorithm. The contour tracer connects and completes these edge fragments. The algorithm is able to follow the course of a contour without any prior knowledge, even if its direction changes erratically. It has been tested successfully in several applications in industrial production testing (for example for controlling an optical range sensor of a 3-D-measurement system in assembly lines).

关键词： Image segmentation computer vision technology Machine vision Robot vision robots Edge detection Image processing Mathematical modeling Computing systems Systems modeling

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ROBUST OBJECT DETECTION UNDER VARIOUS ENVIRONMENTAL-CONDITIONS

ROBUST OBJECT DETECTION UNDER VARIOUS ENVIRONMENTAL-CONDITIO...

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CONF ON intelligent robots AND computer vision 10 : algorithms AND techniques

作者： MAEDA, E ISHII, K NTT Human Interface Labs. (Japan)

ISBN: (纸本)0819407445

We present a method which is robust to environmental conditions, that detects the existence of space filling objects such as cars, people, etc. This method is unaffected by uniform or local variations in image brightness induced by lighting conditions, weather, shadow of other objects such as buildings, trees, clouds, etc. Moreover, it does not depend on the position, size, or background pattern of the regions, or the shapes and color of the objects to be detected. The method consists of the following processes. Normalize brightness of the target and the reference image using mean and variance of the brightness in respective regions. The reference image is the image which represents the background scene without objects and is taken from the same camera position as the target images. Calculate normalized principal component features from both sets of normalized image brightness. Use the features to construct a classifier by statistical learning. The proposed features are determined by the variance and covariance of brightness of both images. They are a better measure of the correspondence of two images than conventional features such as the correlation coefficient of image brightness or statistics calculated from a difference image. The method is applied to car detection in a parking lot. The experimental images were collected over a one year period under various conditions. At least 98% of the cars were always correctly detected. Application to moving-car detection and person detection in a hall are presented. Since the proposed algorithm for object detection is robust under various environmental conditions and is object independent, it is well suited to a wide range of facilities offering automatic surveillance, automatic counting, automatic recognition of scene situation, etc.

关键词： Detection and tracking algorithms Machine vision Environmental sensing robots Robot vision computer vision technology Mahalanobis distance Cameras Error analysis Infrared imaging

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PATTERN-RECOGNITION USING HILBERT-SPACE

PATTERN-RECOGNITION USING HILBERT-SPACE

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11TH CONF ON intelligent robots AND computer vision : algorithms, techniques, AND ACTIVE vision

作者： LIU, Y Savannah State College (United States)

ISBN: (纸本)0819410268

In this paper, we develop a new learning approach, the Hilbert learning. This approach is similar to Fractal learning, but the Fractal part is replaced by Hilbert space. Like the Fractal learning, the first stage is to encode an image to a small vector in the internal space of a learning system. The next stage is to quantize the internal parameter space. The internal space of a Hilbert learning system is defined as follows: A pattern can be interpreted as a representation of a vector in a Hilbert space. Any vectors in a Hilbert space can be expanded. If a vector happens to be in a subspace of a Hilbert space where the dimension L of the subspace is low (order of 10), the vector can be specified by its norm, an L-vector, and the Hermitian operator which spans the Hilbert space. This establishes a mapping from an image space to the internal space P. This mapping converts an input image to a 4-tuple: t (epsilon) P equals (Norm, T, N, L-vector), where T is an operator parameter space, N is a set of integers which specifies the boundary condition. The encoding is implemented by mapping an input pattern into a point in its internal space. We assume that a system uses local search algorithm, i.e., the system adjusts its internal data locally. The search is first conducted for an operator in a parameter space of operators, then an error function (delta) (t) is computed. The algorithm stops at a local minimum of (delta) (t). Finally, the input training set divides the internal space by a quantization procedure.

关键词： Fractal analysis computer vision technology Machine vision Robot vision robots Space operations computer programming Quantization Neural networks Pattern recognition

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REAL-TIME ADAPTIVE vision SERVOING OF A ROBOTIC MANIPULATOR

REAL-TIME ADAPTIVE VISION SERVOING OF A ROBOTIC MANIPULATOR

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11TH CONF ON intelligent robots AND computer vision : algorithms, techniques, AND ACTIVE vision

作者： HOUSHANGI, N Purdue Univ./Calumet (United States)

ISBN: (纸本)0819410268

To make robotic manipulators function intelligently in an application such as flexible manufacturing, sensory feedback from an unknown environment is needed. Visual feedback represents a typical sensing system in which camera images provide feedback information, for instance, in grasping a moving object. Because image processing is time consuming, information about target position can not be obtained instantaneously for the controller. Because of the inherent time delay, the present and future position of the object has to be predicted in real-time. Since the dynamics of the objects are assumed to be unknown, the prediction will be accomplished by means of an auto-regressive discrete-time model. The predicted values and current end-effector position determine the desired trajectory point (subgoal) for the motion. The planner adapts on-line to changes in the target position. The desired trajectory is tracked by the end-effector controller. After grasping the object, problems may arise in controlling the motion of the manipulator due to the mass of the object attached to the gripper. An adaptive controller is proposed to deal with load uncertainty in the object. A simulation program is presented which demonstrates the task of grasping a moving object by a manipulator using visual feedback.

关键词： Robotics Visualization Cameras computer simulations Environmental sensing Image processing Manufacturing Motion models Sensing systems Sensors

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MACHINE SHAPE PERCEPTION - OBJECT RECOGNITION BASED ON NEED-DRIVEN RESOLUTION FLExIBILITY AND CONVEx-HULL CARVING

MACHINE SHAPE PERCEPTION - OBJECT RECOGNITION BASED ON NEED-...

引用

CONF ON intelligent robots AND computer vision 10 : algorithms AND techniques

作者： YEN, S KONDRASKE, G Univ. of Texas/Arlington (United States)

ISBN: (纸本)0819407445

A hierarchical shape decomposition method called Convex-Hull Carving, derived from Sklansky's Concavity Tree and designed to accommodate the incorporation of human flexible resolution visual perception strategies in machine recognition, is proposed. The method characterizes an arbitrary complex shape at multiple hierarchical levels starting from a gross perspective of the entire shape itself, and progressing to decomposed and quantified convex sub-shapes, etc. Calculation complexity and the amount of data to be processed for object recognition applications are reduced. Sklansky's Concavity Tree is a hierarchical arrangement for describing nonconvex shapes. The concavity tree of a shape is defined as a tree describing the hierarchical arrangement of concavities; i.e., concavities within concavities. In the proposed Convex-Hull Carving method, the concavity tree structure is converted to a structure analogous to a chemical molecule. Tree components represent the `atoms' of the molecule and are characterized by their geometric position and a recently defined quantitative shape attribute called the shape quantifier. In addition, the number of hierarchical levels of shape description employed during recognition is driven by: (1) meeting `need to discriminate' criteria; or (2) the determination that all components (`atoms') are convex within predefined acceptance criteria (i.e., no further reduction is possible). The method was implemented to classify a set of two-dimensional aircraft shapes. Results showed that the method is stable with variation of rotation, scaling, and image resolution factors, as well as small viewing angle projection changes.

关键词： Computing systems Image resolution computer vision technology Robot vision robots Object recognition Visual process modeling Molecules Chemical species Data processing

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NEURONAL-MORPHOLOGY OF BIOLOGICAL vision - A BASIS FOR MACHINE vision 10

NEURONAL-MORPHOLOGY OF BIOLOGICAL VISION - A BASIS FOR MACHI...

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CONF ON intelligent robots AND computer vision 10 : NEURAL, BIOLOGICAL, AND 3-D METHODS

作者： GUPTA, MM Univ. of Saskatchewan (Canada)

ISBN: (纸本)0819407453

In this paper, we are concerned with the study of the biological vision system and the emulation of some of its mathematical functions, in both the retinal and visual cortex, for the development of a robust computer vision system. This field of research is not only intriguing, but offers a great challenge to systems scientists in the development of functional algorithms. These functional algorithms can be generalized for further studies for fields such as signal processing, control systems and image processing. Our studies are heavily dependent on the use of neuronal layers and the generalized receptive fields. Building blocks of such neuronal layers and receptive fields may lead to the design of better sensors and better computer vision systems. It is hoped that these studies will lead to the development of better artificial vision systems with applications to vision prosthesis for visually impaired persons, robotic vision, medical imaging, medical sensors, industrial automation, remote sensing, space stations and ocean exploration.

关键词： Visualization Sensors Retina Machine vision Visual cortex Information visualization Brain Computing systems computer vision technology Optical fibers

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Assessment of the performance of computer vision algorithms and parallel architectures (Manuscript Only)

Assessment of the performance of computer vision algorithms ...

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intelligent robots and computer vision x: algorithms and techniques

作者： Sardana, H.K. Ibrahim, Mohammad K. Daemi, M.F. Univ. of Nottingham Nottingham United Kingdom

ISBN: (纸本)0819407445

The performance of the existing algorithms is generally assessed without any considerations to the architecture or technology that would be used for implementation. In many instances, the performance of the algorithms is degraded when they are implemented on a specific architecture. To date no formal assessment method exists that considers the effect of implementation constraints on the performance of the algorithms. In this investigation, the authors present a novel structured approach that can be used in assessing suitability of implementing algorithms on a specific architecture and in the comparison of performance of different architectures. The performance is measured in terms of a figure of merit that combines both accuracy of results and implementation efficiency. Some special considerations are mentioned that can further enhance the performance.

关键词： computer vision

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TExTURE OPERATOR DETERMINATION BY SIMULATED ANNEALING 10

TEXTURE OPERATOR DETERMINATION BY SIMULATED ANNEALING

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CONF ON intelligent robots AND computer vision 10 : NEURAL, BIOLOGICAL, AND 3-D METHODS

作者： KJELL, B WANG, PY George Mason Univ. (United States)

ISBN: (纸本)0819407453

Convolution of textured images with a set of small masks can be used to produce features for texture classification or for image segmentation. These masks are usually picked from a standard set, such as Laws' texture energy operators or the variations discussed by other researchers. In this paper we discuss using simulated annealing to determine an optimum set of masks for particular sets of textures. Initial masks are picked and iteratively improved by using simulated annealing with an appropriate energy function. The masks converge to a final set that minimizes the energy function. We show experimental results with a small set of textures. The masks produced by the method depends on the textures used, and these masks are more effective in discriminating between these textures than the standard masks.

关键词： Convolution algorithms Annealing Image classification Mahalanobis distance computer vision technology Image segmentation Machine vision Robot vision robots

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FAST 2-D HARTLEY TRANSFORM IN 3-D OBJECT REPRESENTATION AND RECOGNITION 10

FAST 2-D HARTLEY TRANSFORM IN 3-D OBJECT REPRESENTATION AND ...

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CONF ON intelligent robots AND computer vision 10 : NEURAL, BIOLOGICAL, AND 3-D METHODS

作者： LEE, DJ RAMIREZ, M MITRA, S Texas Tech Univ. (United States)

ISBN: (纸本)0819407453

In image processing or computer vision, Fourier transform is widely used for frequency- domain analysis. However, Hartley transform can be a very good substitute for the more commonly used Fourier transform when the real input data are concerned. A two-dimensional butterfly algorithm for fast Fourier transform has been modified to calculate the Hartley transform faster than could be done using row-column decomposition. This paper presents three different frequency-domain registration techniques, power cepstrum, complex cepstrum and phase correlation. These techniques not only are capable of precise registration of images but also lead to three-dimensional (3-D) reconstruction of real objects by finding the corresponding points and disparities of an image pair. Use of these recently developed techniques allows one to obtain a precise displacement between two images and a quantitative measurement of 3-D information in a relatively faster computation time. Hartley transform can be used to implement all of these three techniques instead of using complex number computation required by Fourier transform. An additional 35 percent saving of the computation time is achieved by implementing the two-dimensional butterfly algorithm for computing Hartley transform. This reduction in computation time makes the use of Hartley transform in frequency-domain analysis more attractive.

关键词： Fourier transforms Image registration computer vision technology Machine vision 3D image processing Robot vision robots Silicon Image processing Image restoration

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Implementing an integrated approach to planning and reaction

Implementing an integrated approach to planning and reaction

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intelligent robots and computer vision x: algorithms and techniques

作者： Lyons, Damian M. Hendriks, Antonius J. Philips Labs. Briarcliff Manor NY USA

The ability to act flexibly in an uncertain and dynamic environment is one of the key objectives of robotics. In previous work, we described an approach to this problem which we called the planner-reactor approach. Th... 详细信息

ISBN: (纸本)0819407445

关键词： robots, Industrial

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