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Pattern Analysis and Machine Intelligence, IEEE Transactions on

Issue 2 • Date March 1987

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Displaying Results 1 - 23 of 23
  • [Front cover]

    Publication Year: 1987 , Page(s): c1
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  • List of Contributors

    Publication Year: 1987 , Page(s): nil1
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  • [Breaker page]

    Publication Year: 1987 , Page(s): nil1
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  • The Effect of Median Filtering on Edge Estimation and Detection

    Publication Year: 1987 , Page(s): 181 - 194
    Cited by:  Papers (54)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (4275 KB)  

    In this paper we consider the effect of median prefiltering on the subsequent estimation and detection of edges in digital images. Where possible, a quantitative statistical comparison is made for a number of filters defined with two-dimensional geometries; in some cases one-dimensional analyses are required to illustrate certain points. Noise images prefiltered by median filters defined with a variety of windowing geometries are used to support the analysis, and it is found that median prefiltering improves the performance of both thresholding and zero-crossing based edge detectors. View full abstract»

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  • Simple Parallel Hierarchical and Relaxation Algorithms for Segmenting Noncausal Markovian Random Fields

    Publication Year: 1987 , Page(s): 195 - 219
    Cited by:  Papers (92)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (10586 KB)  

    The modeling and segmentation of images by MRF's (Markov random fields) is treated. These are two-dimensional noncausal Markovian stochastic processes. Two conceptually new algorithms are presented for segmenting textured images into regions in each of which the data are modeled as one of C MRF's. The algorithms are designed to operate in real time when implemented on new parallel computer architectures that can be built with present technology. A doubly stochastic representation is used in image modeling. Here, a Gaussian MRF is used to model textures in visible light and infrared images, and an autobinary (or autoternary, etc.) MRF to model a priori information about the local geometry of textured image regions. For image segmentation, the true texture class regions are treated either as a priori completely unknown or as a realization of a binary (or ternary, etc.) MRF. In the former case, image segmentation is realized as true maximum likelihood estimation. In the latter case, it is realized as true maximum a posteriori likelihood segmentation. In addition to providing a mathematically correct means for introducing geometric structure, the autobinary (or ternary, etc.) MRF can be used in a generative mode to generate image geometries and artificial images, and such simulations constitute a very powerful tool for studying the effects of these models and the appropriate choice of model parameters. The first segmentation algorithm is hierarchical and uses a pyramid-like structure in new ways that exploit the mutual dependencies among disjoint pieces of a textured region. View full abstract»

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  • Scene Segmentation from Visual Motion Using Global Optimization

    Publication Year: 1987 , Page(s): 220 - 228
    Cited by:  Papers (90)  |  Patents (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (4988 KB)  

    This paper presents results from computer experiments with an algorithm to perform scene disposition and motion segmentation from visual motion or optic flow. The maximum a posteriori (MAP) criterion is used to formulate what the best segmentation or interpretation of the scene should be, where the scene is assumed to be made up of some fixed number of moving planar surface patches. The Bayesian approach requires, first, specification of prior expectations for the optic flow field, which here is modeled as spatial and temporal Markov random fields; and, secondly, a way of measuring how well the segmentation predicts the measured flow field. The Markov random fields incorporate the physical constraints that objects and their images are probably spatially continuous, and that their images are likely to move quite smoothly across the image plane. To compute the flow predicted by the segmentation, a recent method for reconstructing the motion and orientation of planar surface facets is used. The search for the globally optimal segmentation is performed using simulated annealing. View full abstract»

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  • Optical Flow Estimation: An Error Analysis of Gradient-Based Methods with Local Optimization

    Publication Year: 1987 , Page(s): 229 - 244
    Cited by:  Papers (80)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (4394 KB)  

    Multiple views of a scene can provide important information about the structure and dynamic behavior of three-dimensional objects. Many of the methods that recover this information require the determination of optical flow-the velocity, on the image, of visible points on object surfaces. An important class of techniques for estimating optical flow depend on the relationship between the gradients of image brightness. While gradient-based methods have been widely studied, little attention has been paid to accuracy and reliability of the approach. Gradient-based methods are sensitive to conditions commonly encountered in real imagery. Highly textured surfaces, large areas of constant brightness, motion boundaries, and depth discontinuities can all be troublesome for gradient-based methods. Fortunately, these problematic areas are usually localized can be identified in the image. In this paper we examine the sources of errors for gradient-based techniques that locally solve for optical flow. These methods assume that optical flow is constant in a small neighborhood. The consequence of violating in this assumption is examined. The causes of measurement errors and the determinants of the conditioning of the solution system are also considered. By understanding how errors arise, we are able to define the inherent limitations of the technique, obtain estimates of the accuracy of computed values, enhance the performance of the technique, and demonstrate the informative value of some types of error. View full abstract»

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  • Image Estimation Using Doubly Stochastic Gaussian Random Field Models

    Publication Year: 1987 , Page(s): 245 - 253
    Cited by:  Papers (43)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (4732 KB)  

    The two-dimensional (2-D) doubly stochastic Gaussian (DSG) model was introduced by one of the authors to provide a complete model for spatial filters which adapt to the local structure in an image signal. Here we present the optimal estimator and 2-D fixed-lag smoother for this DSG model extending earlier work of Ackerson and Fu. As the optimal estimator has an exponentially growing state space, we investigate suboptimal estimators using both a tree and a decision-directed method. Experimental results are presented. View full abstract»

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  • The Nearest Neighbor and the Bayes Error Rates

    Publication Year: 1987 , Page(s): 254 - 262
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2219 KB)  

    The (k, l) nearest neighbor method of pattern classification is compared to the Bayes method. If the two acceptance rates are equal then the asymptotic error rates satisfy the inequalities Ek,l + 1 ¿ E*(¿) ¿ Ek,l dE*(¿), where d is a function of k, l, and the number of pattern classes, and ¿ is the reject threshold for the Bayes method. An explicit expression for d is given which is optimal in the sense that for some probability distributions Ek,l and dE* (¿) are equal. View full abstract»

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  • Structuring Free Space as a Hypergraph for Roving Robot Path Planning and Navigation

    Publication Year: 1987 , Page(s): 263 - 273
    Cited by:  Papers (22)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2409 KB)  

    This paper presents a method of structuring the free space of a roving robot's environment into a set of overlapping convex regions ideally suited to path planning and navigation tasks. The structure of the free space environment is maintained as a hypergraph with each convex region represented by a hyperedge identifying the boundary walls of the region. A new methodology reveals the structure of free space and constructs the hypergraph representation through a directed search for a set of fundamental circits in an abstract graphical representation of the environment geometry. View full abstract»

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  • On the Recognition of Printed Characters of Any Font and Size

    Publication Year: 1987 , Page(s): 274 - 288
    Cited by:  Papers (115)  |  Patents (11)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3398 KB)  

    We describe the current state of a system that recognizes printed text of various fonts and sizes for the Roman alphabet. The system combines several techniques in order to improve the overall recognition rate. Thinning and shape extraction are performed directly on a graph of the run-length encoding of a binary image. The resulting strokes and other shapes are mapped, using a shape-clustering approach, into binary features which are then fed into a statistical Bayesian classifier. Large-scale trials have shown better than 97 percent top choice correct performance on mixtures of six dissimilar fonts, and over 99 percent on most single fonts, over a range of point sizes. Certain remaining confusion classes are disambiguated through contour analysis, and characters suspected of being merged are broken and reclassified. Finally, layout and linguistic context are applied. The results are illustrated by sample pages. View full abstract»

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  • Learning and Plan Refinement in a Knowledge-Based System for Automatic Speech Recognition

    Publication Year: 1987 , Page(s): 289 - 305
    Cited by:  Papers (3)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3957 KB)  

    This paper shows how a semiautomatic design of a speech recognition system can be done as a planning activity. Recognition performances are used for deciding plan refinement. Inductive learning is performed for setting action preconditions. Experimental results in the recognition of connected letters spoken by 100 speakers are presented. View full abstract»

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  • A Rule-Based System for Verifying Engineering Specifications in Industrial Visual Inspection Applications

    Publication Year: 1987 , Page(s): 306 - 311
    Cited by:  Papers (7)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1596 KB)  

    An important step in automatic visual inspection is verifying whether a part is good or bad, by comparing a list of inspection specifications to a list of extracted and measured defects. Our goal is to provide a general, flexible, and efficient solution to this problem. We present a solution following a rule-based approach for the case of specs for visual inspection of disk heads. However, due to the generality of our approach (within the realm of visual inspection), it is easily extendible to verification of specs in other visual inspection applications. While flexibility comes naturally with the rule-based approach, efficiency is still an issue. Therefore, we implemented two techniques to increase the efficiency of our system: one at the rule level, and one at the rule-matching level. We describe our implementation and show experimental results from applying our approach in an experimental system for automatic visual disk head inspection. View full abstract»

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  • A Convex Hull Inclusion Test

    Publication Year: 1987 , Page(s): 312 - 316
    Cited by:  Papers (1)
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    A new characterization of the interior of the convex hull of a finite point set is given. An inclusion test based on this characterization is, on average, almost linear in the number of points times the dimensionality. View full abstract»

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  • Digital Parallelism, Perpendicularity, and Rectangles

    Publication Year: 1987 , Page(s): 316 - 321
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1335 KB)  

    The slope of digital line segments is defined and an algorithm to evaluate it is presented. Parallelism and perpendicularity of two digital line segments are also defined. Finally, rectangular digital regions are defined and characterized, and an algorithm that determines whether or not a given digital region is a digital rectangle is presented. View full abstract»

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  • On Extensions to Fisher's Linear Discriminant Function

    Publication Year: 1987 , Page(s): 321 - 325
    Cited by:  Papers (6)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3476 KB)  

    This correspondence describes extensions to Fisher's linear discriminant function which allow both differences in class means and covariances to be systematically included in a process for feature reduction. It is shown how the Fukunaga-Koontz transform can be combined with Fisher's method to allow a reduction of feature space from many dimensions to two. Performance is seen to be superior in general to the Foley-Sammon method. The technique is developed to show how a new radius vector (or pair of radius vectors) can be combined with Fisher's vector to produce a classifier with even more power of discrimination. Illustrations of the technique show that good discrimination can be obtained even if there is considerable overlap of classes in any one projection. View full abstract»

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  • Mobile Robot Localization Using Sonar

    Publication Year: 1987 , Page(s): 325 - 332
    Cited by:  Papers (79)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2646 KB)  

    This correspondence describes a method by which range data from a sonar rangefinder can be used to determine the two-dimensional position and orientation of a mobile robot inside a room. The plan of the room is modeled as a list of segments indicating the positions of walls. The algorithm works by correlating straight segments in the range data against the room model, then eliminating implausible configurations using the sonar barrier test, which exploits physical constraints on sonar data. The approach is extremely tolerant of noise and clutter. Transient objects such as furniture and people need not be included in the room model, and very noisy, low-resolution sensors can be used. The algorithm's performance is demonstrated using a Polaroid Ultrasonic Rangefinder. View full abstract»

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  • A Motion Stereo Method Based on Coarse-to-Fine Control Strategy

    Publication Year: 1987 , Page(s): 332 - 336
    Cited by:  Papers (16)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2576 KB)  

    This correspondence presents a motion stereo method based on coarse-to-fine control strategy. A camera sliding straight takes images that form a set of stereo pairs. The matching proceeds from the shortest baseline pair to the longest baseline pair, using the disparity map already obtained to guide in searching for the next pair. View full abstract»

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  • [Advertisement]

    Publication Year: 1987 , Page(s): 337 - 338
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  • [Advertisement]

    Publication Year: 1987 , Page(s): 339
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  • Call for Papers

    Publication Year: 1987 , Page(s): 340
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  • List of Contributors

    Publication Year: 1987 , Page(s): nil2
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    Freely Available from IEEE
  • [Front cover]

    Publication Year: 1987 , Page(s): c2
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    Freely Available from IEEE

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