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Pattern Analysis and Machine Intelligence, IEEE Transactions on

Issue 4 • Date July 1984

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  • [Front cover]

    Page(s): c1
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  • List of Contributors

    Page(s): nil1
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  • [Breaker page]

    Page(s): nil1
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  • Opinion

    Page(s): 385
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  • Research on Machine Recognition of Handprinted Characters

    Page(s): 386 - 405
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    Machine recognition of handprinted Chinese characters has recently become very active in Japan. Both from the practical and the academic point of view, very encouraging results are reported. The work is described systematically and analyzed in terms of so-called feature matching, which is likely to be the mainstream of the research and development of machine recognition of handprinted Chinese characters. A database, ETL8 (881 Kanji, 71 hirakana, and 160 variations for each category), is explained, on which many experiments were performed. Recognition rates reported using this database can be compared, and so somewhat qualitative evaluation of these methods is described. Based on the comparative study, the merits and demerits of both feature and structural matching are discussed and some future directions are mentioned. View full abstract»

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  • Analysis and Design of a Decision Tree Based on Entropy Reduction and Its Application to Large Character Set Recognition

    Page(s): 406 - 417
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    Based on a recursive process of reducing the entropy, the general decision tree classifier with overlap has been analyzed. Several theorems have been proposed and proved. When the number of pattern classes is very large, the theorems can reveal both the advantages of a tree classifier and the main difficulties in its implementation. Suppose H is Shannon's entropy measure of the given problem. The theoretical results indicate that the tree searching time can be minimized to the order O(H), but the error rate is also in the same order O(H) due to error accumulation. However, the memory requirement is in the order 0(H exp(H)) which poses serious problems in the implementation of a tree classifier for a large number of classes. To solve these problems, several theorems related to the bounds on the search time, error rate, memory requirement and overlap factor in the design of a decision tree have been proposed and some principles have been established to analyze the behaviors of the decision tree. When applied to classify sets of 64, 450, and 3200 Chinese characters, respectively, the experimental results support the theoretical predictions. For 3200 classes, a very high recognition rate of 99.88 percent was achieved at a high speed of 873 samples/s when the experiment was conducted on a Cyber 172 computer using a high-level language. View full abstract»

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  • Bayesian Recognition of Local 3-D Shape by Approximating Image Intensity Functions with Quadric Polynomials

    Page(s): 418 - 429
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    The recognition in image data of viewed patches of spheres, cylinders, and planes in the 3-D world is discussed as a first step to complex object recognition or complex object location and orientation estimation. Accordingly, an image is partitioned into small square windows, each of which is a view of a piece of a sphere, or of a cylinder, or of a plane. Windows are processed in parallel for recognition of content. New concepts and techniques include approximations of the image within a window by 2-D quadric polynomials where each approximation is constrained by one of the hypotheses that the 3-D surface shape seen is either planar, cylindrical, or spherical; a recognizer based upon these approximations to determine whether the object patch viewed is a piece of a sphere, or a piece of a cylinder, or a piece of a plane; lowpass filtering of the image by the approximation. The shape recognition is computationally simple, and for large windows is approximately Bayesian minimum-probability-of-error recognition. These classifications are useful for many purposes. One such purpose is to enable a following processor to use an appropriate estimator to estimate shape, and orientation and location parameters for the 3-D surface seen within a window. View full abstract»

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  • 3-D Space Location and Orientation Parameter Estimation of Lambertian Spheres and Cylinders From a Single 2-D Image By Fitting Lines and Ellipses to Thresholded Data

    Page(s): 430 - 441
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    An approach to object location and orientation estimation is discussed in which objects in 3-D space are approximated by chunks of spheres, cylinders, and planes. The surface-shape parameters of these chunks of primitive subobjects are estimated in real time from a single 2-D image assuming a Lambertian reflection model. This processing is realized by partitioning an image into small square windows and processing the windows in parallel. It is assumed that a small window views a portion of one of the spherical, cylindrical or planar chunks. The paper applies standard statistical estimators in new ways to the estimation of the 3-D shape parameters for spherical and cylindrical surfaces. Linear regression and scatter matrix eigenvalue analysis techniques are used here. The algorithms are computationally simple yet are robust and can handle noisy highly variable data. View full abstract»

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  • Two-Dimensional Critical Point Configuration Graphs

    Page(s): 442 - 450
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    The configuration of the critical points of a smooth function of two variables is studied under the assumption that the function is Morse, that is, that all of its critical points are nondegenerate. A critical point configuration graph (CPCG) is derived from the critical points, ridge lines, and course lines of the function. Then a result from the theory of critical points of Morse functions is applied to obtain several constraints on the number and type of critical points that appear on cycles of a CPCG. These constraints yield a catalog of equivalent CPCG cycles containing four entries. The slope districts induced by a critical point configuration graph appear useful for describing the behavior of smooth functions of two variables, such as surfaces, images, and the radius function of three-dimensional symmetric axes. View full abstract»

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  • Discrete Representation of Straight Lines

    Page(s): 450 - 463
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    If a continuous straight line segment is digitized on a regular grid, obviously a loss of information occurs. As a result, the discrete representation obtained (e.g., a chaincode string) can be coded more conveniently than the continuous line segment, but measurements of properties (such as line length) performed on the representation have an intrinsic inaccuracy due to the digitization process. In this paper, two fundamental properties of the quantization of straight line segments are treated. 1) It is proved that every ``straight'' chaincode string can be represented by a set of four unique integer parameters. Definitions of these parameters are given. 2) A mathematical expression is derived for the set of all continuous line segments which could have generated a given chaincode string. The relation with the chord property is briefly discussed. View full abstract»

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  • Multiprocessor Pyramid Architectures for Bottom-Up Image Analysis

    Page(s): 463 - 475
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    This paper describes three hierarchical organizations of small processors for bottom-up image analysis:pyramids, interleaved pyramids, and pyramid trees. Progressively lower levels in the hierarchies process image windows of decreasing size. Bottom-up analysis is made feasible by transmitting up the levels quadrant borders and border-related information that captures quadrant interaction of interest for a given computation. The operation of the pyramid is illustrated by examples of standard algorithms for interior-based computations (e.g., area) and border-based computations of local properties (e.g., perimeter). A connected component counting algorithm is outlined that illustrates the role of border-related information in representing quadrant interaction. Interleaved pyramids are obtained by sharing processors among several pyramids. They increase processor utilization and throughput rate at the cost of increased hardware. Trees of shallow interleaved pyramids, calld pyramid trees, are introduced to reduce the hardware requirements of large interleaved pyramids at the expense of increased processing time, without sacrificing processor utilization. The three organizations are compared with respect to several performance measures. View full abstract»

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  • Picture Indexing and Abstraction Techniques for Pictorial Databases

    Page(s): 475 - 484
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    We present an approach for picture indexing and abstraction. Picture indexing facilitates information retrieval from a pictorial database consisting of picture objects and picture relations. To construct picture indexes, abstraction operations to perform picture object clustering and classification are formulated. To substantiate the abstraction operations, we also formalize syntactic abstraction rules and semantic abstraction rules. We then illustrate by examples how to apply these abstraction operations to obtain various picture indexes, and how to construct icons to facilitate accessing of pictorial data. View full abstract»

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  • Database Structure and Manipulation Capabilities of a Picture Database Management System (PICDMS)

    Page(s): 484 - 492
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    The database structure and data manipulation capabilities of a generalized PICture Database Management System (PICDMS) are presented. They are based on a dynamic, stacked-image, logical database structure that uses gridded, rather than topological, data representation. A prototype PICDMS has been designed and implemented. A commercial version is being used as a generator of image processing programs. The system has novel capabilities for nonprogrammer users: it is able to 1) build multiple-variable databases from photographs and other two-dimensional data sources such as maps, drawings, etc., and 2) manipulate such data using simple logical commands. Physical organization and accessing strategies are outlined. A summary of the PICDMS data manipulation capabilities is presented and a subset of operations is illustrated with brief examples. A comprehensive example displays PICDMS capabilities and the programming advantages it possesses over other approaches. View full abstract»

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  • Word-Meaning Selection in Multiprocess Language Understanding Programs

    Page(s): 493 - 509
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    An understander reading or listening to someone speak has to repeatedly solve the problem of word-meaning ambiguity, the selection of the intended meaning of a word from the set of its possible meanings. For example, the problem of pronominal reference can be considered as a choosing of the intended referent from the collection of entities which have already been mentioned or which can be inferred. Human understanders apply rules of syntax, surface semantics, general world knowledge, and various types of contextual knowledge to resolve word-sense or pronominal ambiguity as they process language. We describe a mechanism, called a cooperative word-meaning selector, which allows the computer to use various knowledge sources as it ``understands'' text. The word-meaning selector is part of a conceptual analyzer which forms the natural-language interface for a pair of multiprocess language processing systems. The first, called DSAM (distributable script applier mechanism), reads and summarizes newspaper articles making heavy reference to situational scripts. The second, ACE (academic counseling experiment), is a conversational program which automates certain parts of the academic counseling task. In each of these systems, a variety of knowledge sources, each managed by a distinct ``expert'' process, is brought to bear to enable the word-meaning selector to form the most plausible reading of a sentence containing ambiguous words. View full abstract»

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  • Solving Satisfiability with Less Searching

    Page(s): 510 - 513
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    A new technique, complement searching, is given for reducing the amount of searching required to solve satisfiability (constraint satisfaction) problems. Search trees for these problems often contain subtrees that have approximately the same shape. When this occurs, knowledge that the first subtree does not have a solution can be used to reduce the searching in the second subtree. Only the part of the second subtree which is different from the first needs to be searched. The pure literal rule of the Davis-Putnam procedure is a special case of complement searching. The new technique greatly reduces the amount of searching required to solve conjunctive normal form predicates that contain almost pure literals (literals with a small number of occurrences). View full abstract»

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  • Matching Three-Dimensional Objects Using Silhouettes

    Page(s): 513 - 518
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    A method for matching three-dimensional objects against a library of models from an observed sequence of silhouettes is presented in this correspondence. Based upon the observed silhouettes, the three-dimensional structure of the object is constructed and refined. The principal moments and three primary silhouettes are computed for the constructed three-dimensional objects to represent the aggregate and detailed structure parameters. The adaptive matching technique requires that sufficient silhouettes be added to modify the structure of the unknown object until consistent and steady matching results are obtained. The library for matching is based on three primary silhouettes of the model objects. Experiments conducted show a fast convergence to a consistent result may be achieved provided that a reasonable choice of silhouettes is made. View full abstract»

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  • Multiple Resolution Texture Analysis and Classification

    Page(s): 518 - 523
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    Textures are classified based on the change in their properties with changing resolution. The area of the gray level surface is measured at serveral resolutions. This area decreases at coarser resolutions since fine details that contribute to the area disappear. Fractal properties of the picture are computed from the rate of this decrease in area, and are used for texture comparison and classification. The relation of a texture picture to its negative, and directional properties, are also discussed. View full abstract»

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  • Determining Motion Parameters for Scenes with Translation and Rotation

    Page(s): 523 - 530
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    A study of methods that determine the rotation parameters of a camera moving through synthetic and real scenes is conducted. Algorithms that combine ideas of Jain and Prazdny, using hypothesizeand-verify paradigm, are developed to find translational and rotational parameters. An argument is made for using hypothesized motion parameters rather than relaxation labeling to find correspondence. Some work with real scenes shows the difficulties introduced by noise, the lack of resolution, and the need for better low-level techniques. View full abstract»

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  • A Posteriori Estimation of Correlated Jointly Gaussian Mean Vectors

    Page(s): 530 - 535
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    This paper describes the use of maximum a posteriori probability (MAP) techniques to estimate the mean values of features used in statistical pattern classification problems, when these mean feature values from the various decision classes are jointly Gaussian random vectors that are correlated across the decision classes. A set of mathematical formalisms is proposed and used to derive closed-form expressions for the estimates of the class-conditional mean vectors, and for the covariance matrix of the errors of these estimates. Finally, the performance of these algorithms is described for the simple case of a two-class one-feature pattern recognition problem, and compared to the performance of classical estimators that do not exploit the class-to-class correlations of the features' mean values. View full abstract»

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  • Estimation of Error Rates in Classification of Distorted Imagery

    Page(s): 535 - 542
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    This correspondence considers the problem of matching image data to a large library of objects when the image is distorted. Two types of distortions are considered: blur-type, in which a transfer function is applied to Fourier components of the image, and scale-type, in which each Fourier component is mapped into another. The objects of the library are assumed to be normally distributed in an appropriate feature space. Approximate expressions are developed for classification error rates as a function of noise. The error rates they predict are compared with those from classification of artificial data, generated by a Gaussian random number generator, and with error rates from classification of actual data. It is demonstrated that, for classification purposes, distortions can be characterized by a small number of parameters. View full abstract»

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  • Call for Papers

    Page(s): 543
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  • Call for Papers

    Page(s): 544
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  • List of Contributors

    Page(s): nil2
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  • [Front cover]

    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.

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Meet Our Editors

Editor-in-Chief
David A. Forsyth
University of Illinois