A general framework for using artificial neural networks in the recognition of 3-D objects from a single view is provided. An autonomous 3-D object recognition system based on the theories of superquadrics and fractal...
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ISBN:
(纸本)0818621087
A general framework for using artificial neural networks in the recognition of 3-D objects from a single view is provided. An autonomous 3-D object recognition system based on the theories of superquadrics and fractals is presented. these theories are conbined with artificial neural network models.
the authors explore three aspects of curved 3-D object recognition from monocular image contours: quantitative interpretation of contour position, orientation, and curvature;qualitative prediction of contour topology ...
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ISBN:
(纸本)0818621087
the authors explore three aspects of curved 3-D object recognition from monocular image contours: quantitative interpretation of contour position, orientation, and curvature;qualitative prediction of contour topology in the form of exact aspect graphs;and hybrid interpretation of contour features such as cusps, inflections, and t-junctions. Preliminary results are presented.
this work focuses on the ultrasonic feature-mapping technique for post-factum control. Feature-based analysis and material state imaging constitute a powerful technique, applying both physically and statistically base...
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this work focuses on the ultrasonic feature-mapping technique for post-factum control. Feature-based analysis and material state imaging constitute a powerful technique, applying both physically and statistically based principles. the technique integrates many data collection procedures, such as critical angles, surface waves, plate waves, and backscattering techniques, into an extremely versatile data acquisition protocol and entails detailed analysis through state-of-the-technology signal processing, patternrecognition, and system and/or artificial intelligence implementation practice. the various existing possibilities for physically based data collection and the types of feature domains and features available for anomaly representation in materials are discussed. Possible applications of feature-based imaging in a manufacturing environment through post factum quality control are considered.< >
the linear systems in a saturated mode (LSSM) model is applied to Korean character recognition. In general, conventional neural networks without uncommitted neurons cannot incorporate new patterns for recognition, and...
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the linear systems in a saturated mode (LSSM) model is applied to Korean character recognition. In general, conventional neural networks without uncommitted neurons cannot incorporate new patterns for recognition, and patternrecognition and reconstruction of many learned patterns cannot be performed simultaneously. It is shown that these problems can be solved by using a colored neural net model.< >
A theory for computational geometry appropriate for geometrical objects specified by point sets (in effect, binary images) is developed. the theory deals withthe determination of the transformation that brings two im...
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A theory for computational geometry appropriate for geometrical objects specified by point sets (in effect, binary images) is developed. the theory deals withthe determination of the transformation that brings two images into registration, and the similarity of optimally registered sets. Several classes of geometric transformations are considered: translation, congruence, and similarity transformations. the theory is based on 'potential functions,' which are shift- and rotation-invariant set comparison functions that are generalizations of cross-correlation and set difference. these functions have the advantage of 'action at a distance,' which facilitates matching of nonoverlapping sets. the type of set comparison function that is admissable depends on the class of transformations under consideration. A relation between potential functions and the use of moments for registration is discovered.< >
the problem of advancing machine visual patternrecognition capabilities is approached by examining the visual system of the primate. A model of biological vision is suggested, and an analogous machine vision simulati...
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the problem of advancing machine visual patternrecognition capabilities is approached by examining the visual system of the primate. A model of biological vision is suggested, and an analogous machine vision simulation is developed. the modeling is limited to luminance information (color, motion, and depth are not considered), and biological systems are considered at the network level (biochemical and biophysical details are not simulated). the system architecture consists of a set of invariance transforms (luminance, spatial, and scale) followed by storage using an adaptive resonance theory network.< >
the potential of acoustic emission (AE) as a method of intelligent process monitoring is explored. It is shown that a number of tools are available to the user of acoustic emission, making it possible to apply the tec...
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the potential of acoustic emission (AE) as a method of intelligent process monitoring is explored. It is shown that a number of tools are available to the user of acoustic emission, making it possible to apply the technique to a variety of problems. By way of example, the authors discuss a laboratory study in which acoustic emission events from a fatigue test are monitored and a large number of selected signals are digitally recorded. the event trends and signals are analyzed in order to discriminate between acoustic events associated with material defects and those produced by other benign sources. By the use of both physical arguments and patternrecognition techniques which are empirical or statistical in nature, these results are related to the failure processes taking place within the specimen.< >
One of the goals of research for the last two decades or so in patternrecognition and its subareas (such as imageprocessing, analysis and understanding, speech processing, analysis and understanding, natural-languag...
One of the goals of research for the last two decades or so in patternrecognition and its subareas (such as imageprocessing, analysis and understanding, speech processing, analysis and understanding, natural-language processing and understanding, computer vision techniques, etc.) has been to develop fundamental techniques for flexible interactive intelligent man-machine interfaces for computers. the author argues that the evolution to the fifth-generation computer systems (FGCS), as defined by Japanese scientists, will require, among other things, advances in patternrecognition and its subareas, not only to achieve man-machine interfaces with a natural mode of communication, but also to implement the basic mechanisms of inference, association and learning, which are inherent in patternrecognition and therefore essential to the core functions of FGCS. the next-generation computers will be knowledge-based systems, which constitute a subdomain of artificial-intelligence (AI) techniques and so AI provides the essential link between the abovementioned pattern-recognition domains and different application systems. After introducing a natural and intrinsic link between the evolving subjects of AI and computer-vision research, particularly in the context of the next generation of computer-system research, the paper presents an overview of the framework of current image-understanding research from the points of view of knowledge level, information level, and complexity. Because a general-purpose computer-vision system must be capable of recognizing 3-D objects, the paper attempts to define the 3-D object-recognition problem and discusses basic concepts associated withthis problem. the major application areas often are industrial vision systems and scene analysis in aerial photography. No attempt is made to discuss other essential conceptual building blocks, such as software engineering, computer architecture, and VLSI technology, unless these become especially relevant
Current research in range sensors and range data processing for application to intelligent, sensory directed, robotic systems is discussed. A number of related range image types are described along with typical techni...
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ISBN:
(纸本)0903608960
Current research in range sensors and range data processing for application to intelligent, sensory directed, robotic systems is discussed. A number of related range image types are described along with typical techniques used to acquire the images. Some example range images are shown and their characteristics are related along with a discussion of computational complexities involved in the use of such data within practical robotic systems. An application of range imageprocessing to robotic spray painting is examined to illustrate the problems.
A system that combines basic imageprocessing functions and PROLOG is outlined. PROLOG allows descriptions of objects, images, and rules about the problem domain to be defined by logical statements with an English-lik...
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ISBN:
(纸本)0903608960
A system that combines basic imageprocessing functions and PROLOG is outlined. PROLOG allows descriptions of objects, images, and rules about the problem domain to be defined by logical statements with an English-like interpretation. these statements may be used to solve imageprocessing problems by direct interpretation by PROLOG. three examples in inspection and part location show techniques of matching descriptions, symbolic 2D transforms and hypothesis verification.
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