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IEEE Transactions on Pattern Analysis and Machine Intelligence

Issue 7 • Date Jul 1992

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Displaying Results 1 - 7 of 7
  • On achievable accuracy in edge localization

    Publication Year: 1992, Page(s):777 - 781
    Cited by:  Papers (32)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (436 KB)

    Edge localization occurs when an edge detector determines the location of an edge in an image. The authors use statistical parameter estimation techniques to derive bounds on achievable accuracy in edge localization. These bounds, known as the Cramer-Rao bounds, reveal the effect on localization of factors such as signal-to-noise ratio (SNR), extent of edge observed, scale of smoothing filter, and... View full abstract»

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  • Computerized flow field analysis: oriented texture fields

    Publication Year: 1992, Page(s):693 - 709
    Cited by:  Papers (109)  |  Patents (4)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2064 KB)

    An approach to the solution of signal-to-symbol transformation in the domain of flow fields, such as oriented texture fields and velocity vector fields, is discussed. The authors use the geometric theory of differential equations to derive a symbol set based on the visual appearance of phase portraits which are a geometric representation of the solution curves of a system of differential equations... View full abstract»

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  • Compact object recognition using energy-function-based optimization

    Publication Year: 1992, Page(s):770 - 777
    Cited by:  Papers (23)  |  Patents (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1824 KB)

    Describes a method of recognizing objects whose contours can be represented in smoothly varying polar coordinate form. Both low- and high-level information about the object (contour smoothness and edge sharpness at the low level and contour shape at the high level) are incorporated into a single energy function that defines a 1D, cyclic, Markov random field (1DCMRF). This 1DCMRF is based on a pola... View full abstract»

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  • On piecewise-linear classification

    Publication Year: 1992, Page(s):782 - 786
    Cited by:  Papers (14)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (480 KB)

    The authors make use of a real data set containing 9-D measurements of fine needle aspirates of a patient's breast for the purpose of classifying a tumor's malignancy for which early stopping in the generation of the separating hyperplanes is not appropriate. They compare a piecewise-linear classification method with classification based on a single linear separator. A precise methodology for comp... View full abstract»

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  • Characterization of signals from multiscale edges

    Publication Year: 1992, Page(s):710 - 732
    Cited by:  Papers (1840)  |  Patents (60)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2384 KB)

    A multiscale Canny edge detection is equivalent to finding the local maxima of a wavelet transform. The authors study the properties of multiscale edges through the wavelet theory. For pattern recognition, one often needs to discriminate different types of edges. They show that the evolution of wavelet local maxima across scales characterize the local shape of irregular structures. Numerical descr... View full abstract»

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  • Object and texture classification using higher order statistics

    Publication Year: 1992, Page(s):733 - 750
    Cited by:  Papers (66)  |  Patents (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1464 KB)

    The problem of the detection and classification of deterministic objects and random textures in a noisy scene is discussed. An energy detector is developed in the cumulant domain by exploiting the noise insensitivity of higher order statistics. An efficient implementation of this detector is described, using matched filtering. Its performance is analyzed using asymptotic distributions in a binary ... View full abstract»

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  • The Meta-Pi network: building distributed knowledge representations for robust multisource pattern recognition

    Publication Year: 1992, Page(s):751 - 769
    Cited by:  Papers (40)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2000 KB)

    The authors present the Meta-Pi network, a multinetwork connectionist classifier that forms distributed low-level knowledge representations for robust pattern recognition, given random feature vectors generated by multiple statistically distinct sources. They illustrate how the Meta-Pi paradigm implements an adaptive Bayesian maximum a posteriori classifier. They also demonstrate its performance i... View full abstract»

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Aims & Scope

The IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) is published monthly. Its editorial board strives to present most important research results in areas within TPAMI's scope.

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Meet Our Editors

Editor-in-Chief
David A. Forsyth
University of Illinois
e-mail: daf@illinois.edu