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IEEE Transactions on Pattern Analysis and Machine Intelligence

Issue 4 • July 1980

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Displaying Results 1 - 17 of 17
  • [Front cover]

    Publication Year: 1980, Page(s): c1
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  • List of Contributors

    Publication Year: 1980, Page(s): nil1
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  • [Breaker page]

    Publication Year: 1980, Page(s): nil1
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  • Bicriterion Cluster Analysis

    Publication Year: 1980, Page(s):277 - 291
    Cited by:  Papers (44)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (3218 KB)

    Cluster analysis is concerned with the problem of partitioning a given set of entities into homogeneous and well-separated subsets called clusters. The concepts of homogeneity and of separation can be made precise when a measure of dissimilarity between the entities is given. Let us define the diameter of a partition of the given set of entities into clusters as the maximum dissimilarity between a... View full abstract»

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  • A Nonparametric Algorithm for Detecting Clusters Using Hierarchical Structure

    Publication Year: 1980, Page(s):292 - 300
    Cited by:  Papers (15)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2169 KB)

    The present paper discusses a nonparametric algorithm for detecting clusters. In the algorithm a positive value called potential is associated with each datum based on dissimilarities. By defining subordination relations among data, hierarchical structure is introduced into the data set. As a result of the introduction of hierarchical structure, the data set is divided into some subsets called sub... View full abstract»

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  • Algorithms for Shape Analysis of Contours and Waveforms

    Publication Year: 1980, Page(s):301 - 312
    Cited by:  Papers (202)  |  Patents (13)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (5086 KB)

    Algorithms for shape analysis are reviewed and classified under various criteria, whether they examine the boundary only or the whole area and whether they describe the original picture in terms of scalar measurements or through structural descriptions. The emphasis is on methodologies which have been popular during the last five years and among them, those which are information preserving. View full abstract»

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  • The Selection of Critical Subsets for Signal, Image, and Scene Matching

    Publication Year: 1980, Page(s):313 - 322
    Cited by:  Papers (5)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (3725 KB)

    A basic matching problem consists of locating a reference subset in a larger set of data subject to a given criterion. Variations of the problem include template matching for object recognition, matched filtering for signal detection, image registration, change detection, cartography feature location, correlation guidance, and scene matching. In the general case the data sets may be made by comple... View full abstract»

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  • Decorrelation Methods of Texture Feature Extraction

    Publication Year: 1980, Page(s):323 - 332
    Cited by:  Papers (74)  |  Patents (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (6625 KB)

    This paper presents the development and evaluation of a visual texture feature extraction method based on a stochastic field model of texture. Results of recent visual texture discrimination experiments are reviewed in order to establish necessary and sufficient conditions for texture features that are in agreement with human discrimination. A texture feature extraction technique involving autocor... View full abstract»

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  • Disparity Analysis of Images

    Publication Year: 1980, Page(s):333 - 340
    Cited by:  Papers (444)  |  Patents (4)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (4752 KB)

    An algorithm for matching images of real world scenes is presented. The matching is a specification of the geometrical disparity between the images and may be used to partially reconstruct the three-dimensional structure of the scene. Sets of candidate matching points are selected independently in each image. These points are the locations of small, distinct features which are likely to be detecta... View full abstract»

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  • Random Graphs: Structural-Contextual Dichotomy

    Publication Year: 1980, Page(s):341 - 348
    Cited by:  Papers (19)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2226 KB)

    A formal definition of random graphs is introduced which is applicable to graphical pattern recognition problems. The definition is used to formulate rigorously the structural-contextual dichotomy of random graphs. The probability of outcome graphs is expressed as the product of two terms, one due to the statistical variability of structure among the outcome graphs and the other due to their conte... View full abstract»

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  • Pattern Recognition as Rule-Guided Inductive Inference

    Publication Year: 1980, Page(s):349 - 361
    Cited by:  Papers (178)  |  Patents (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2982 KB)

    The determination of pattern recognition rules is viewed as a problem of inductive inference, guided by generalization rules, which control the generalization process, and problem knowledge rules, which represent the underlying semantics relevant to the recognition problem under consideration. The paper formulates the theoretical framework and a method for inferring general and optimal (according ... View full abstract»

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  • A New Probabilistic Relaxation Scheme

    Publication Year: 1980, Page(s):362 - 369
    Cited by:  Papers (124)  |  Patents (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (4814 KB)

    Let a vector of probabilities be associated with every node of a graph. These probabilities define a random variable representing the possible labels of the node. Probabilities at neighboring nodes are used iteratively to update the probabilities at a given node based on statistical relations among node labels. The results are compared with previous work on probabilistic relaxation labeling, and e... View full abstract»

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  • New Methods for Picture Reconstruction: Recursive and Causal Techniques

    Publication Year: 1980, Page(s):369 - 376
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2325 KB)

    The methods proposed by Kashyap and Mittal [1], [2] for the reconstruction of pictures from projections are reformulated under a regression model. These reinterpretations are based on least-squares and Bayesian formulations of a statistical linear model and lead to the derivation of recursive and causal algorithms which are more efficient. Experimental results with simulation of the filters are al... View full abstract»

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  • [Advertisement]

    Publication Year: 1980, Page(s):377 - 379
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    Freely Available from IEEE
  • Call for Papers

    Publication Year: 1980, Page(s): 380
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  • List of Contributors

    Publication Year: 1980, Page(s): nil2
    Request permission for commercial reuse | PDF file iconPDF (156 KB)
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  • [Front cover]

    Publication Year: 1980, Page(s): c2
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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.

Full Aims & Scope

Meet Our Editors

Editor-in-Chief
Sven Dickinson
University of Toronto
e-mail: sven@cs.toronto.edu