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Pattern Analysis and Machine Intelligence, IEEE Transactions on

Issue 10 • Date Oct 1993

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Displaying Results 1 - 12 of 12
  • Hierarchical decomposition and axial shape description

    Page(s): 973 - 981
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (844 KB)  

    A method for producing a segmented axial description of a given shape together with a hierarchical decomposition of the shape into its parts is presented. The novelty of this approach lies in the combination of several competing approaches and tools into a unified scheme and an efficient implementation producing natural descriptions. Smooth local symmetries are used for the axial description of parts, which are suggested by curvature sign changes. Parallel symmetries are used to provide information on global relationships within the shape. This information is used for parsing shape into a hierarchy of parts. This approach uses both region and contour information, can handle shapes with corners, and addresses the issue of local versus global information, the issue of scale, and the notion of part. The method is computationally efficient, robust, and stable. Results that show that it provides an intuitive shape description are included View full abstract»

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  • Probabilistic analysis of regularization

    Page(s): 982 - 995
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    In order to use interpolated data wisely, it is important to have reliability and confidence measures associated with it. A method for computing the reliability at each point of any linear functional of a surface reconstructed using regularization is presented. The proposed method is to define a probability structure on the class of possible objects and compute the variance of the corresponding random variable. This variance is a natural measure for uncertainty, and experiments have shown it to correlate well with reality. The probability distribution used is based on the Boltzmann distribution. The theoretical part of the work utilizes tools from classical analysis, functional analysis, and measure theory on function spaces. The theory was tested and applied to real depth images. It was also applied to formalize a paradigm of optimal sampling, which was successfully tested on real depth images View full abstract»

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  • Image representation via a finite Radon transform

    Page(s): 996 - 1006
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    A model of finite Radon transforms composed of Radon projections is presented. The model generalizes to finite group projections in the classical Radon transform theory. The Radon projector averages a function on a group over cosets of a subgroup. Reconstruction formulae that were formally similar to the convolved backprojection ones are derived, and an iterative reconstruction technique is found to converge after a finite number of steps. Applying these results to the group Z2P, new computationally favorable image representations have been obtained. A numerical study of the transform coding aspects is attached View full abstract»

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  • Effective scale: a natural unit for measuring scale-space lifetime

    Page(s): 1068 - 1074
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    A manner in which a notion of effective scale can be introduced in a formal way is developed. For continuous signals, a scaling argument directly gives a natural unit for measuring scale-space lifetime in terms of the logarithm of the ordinary scale parameter. That approach is, however, not appropriate for discrete signals since an infinite lifetime would be assigned to structures existing in the original signal. It is shown how such an effective scale parameter can be defined to give consistent results for both discrete and continuous signals. The treatment is based on the assumption that the probability that a local extremum disappears during a short-scale interval should not vary with scale. As a tool for the analysis, estimates are given of how the density of local extrema can be expected to vary with scale in the scale-space representation of different random noise signals both in the continuous and discrete cases View full abstract»

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  • On functionals with greyvalue-controlled smoothness terms for determining optical flow

    Page(s): 1074 - 1079
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    The modification by H.H. Nagel (1987) of the approach developed by B.K.P. Horn and B.G. Schunck (1981) for determining optical flow is generalized to the case where local motion information is given by more than one constraint equation. Applying this scheme to three constraint equations reported in the literature, as a special case, a generalization of Nagel's approach is obtained. An existence and uniqueness result of solutions under very general conditions that, in turn, ensures the applicability of standard techniques to compute an approximate solution is presented View full abstract»

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  • Local surface shape estimation of 3-D textured surfaces using Gaussian Markov random fields and stereo windows

    Page(s): 1091 - 1098
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    The problem of extracting the local shape information of a 3-D texture surface from a single 2-D image by tracking the perceived systematic deformations the texture undergoes by virtue of being present on a 3-D surface and by virtue of being imaged is examined. The surfaces of interest are planar and developable surfaces. The textured objects are viewed as originating by laying a rubber planar sheet with a homogeneous parent texture on it onto the objects. The homogeneous planar parent texture is modeled by a stationary Gaussian Markov random field (GMRF). A probability distribution function for the texture data obtained by projecting the planar parent texture under a linear camera model is derived, which is an explicit function of the parent GMRF parameters, the surface shape parameters. and the camera geometry. The surface shape parameter estimation is posed as a maximum likelihood estimation problem. A stereo-windows concept is introduced to obtain a unique and consistent parent texture from the image data that, under appropriate transformations, yields the observed texture in the image. The theory is substantiated by experiments on synthesized as well as real images of textured surfaces View full abstract»

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  • Direct gray-scale extraction of features for character recognition

    Page(s): 1053 - 1067
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1452 KB)  

    A method for feature extraction directly from gray-scale images of scanned documents without the usual step of binarization is presented. This approach eliminates binarization by extracting features directly from gray-scale images. In this method, a digitized gray-scale image is treated as a noisy sampling of the underlying continuous surface and desired features are obtained by extracting and assembling topographic characteristics of this surface. The advantages and effectiveness of the approach are both shown theoretically and demonstrated through preliminary experiments of the proposed method View full abstract»

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  • On the calculation of fractal features from images

    Page(s): 1087 - 1090
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    Fractal geometry is becoming increasingly more important in the study of image characteristics. There are numerous methods available to estimate parameters from images of fractal surfaces. A very general technique to calculate numerous fractal features involves the estimation of the mass density function by box counting. The authors analyze the box-counting method, establish a lower bound for the box size, and indicate how algorithms can be improved to give better estimates of fractal features of images. This provides a theoretical basis for a heuristic approach used by C.A. Pickover and A.L. Khorasani (1986) View full abstract»

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  • Face recognition: features versus templates

    Page(s): 1042 - 1052
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    Two new algorithms for computer recognition of human faces, one based on the computation of a set of geometrical features, such as nose width and length, mouth position, and chin shape, and the second based on almost-gray-level template matching, are presented. The results obtained for the testing sets show about 90% correct recognition using geometrical features and perfect recognition using template matching View full abstract»

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  • Determining the axis of a surface of revolution using tactile sensing

    Page(s): 1079 - 1087
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    Dextrous robot hands need to be able to determine the pose of objects to reliably grasp and manipulate them. The first contacts with an object can be used to provide an initial estimate of this information if the object is constrained to be of a particular class. The authors consider a simple example of exploiting class constraints: finding the axis of an unknown surface of revolution. Three tactile curvature measurements on a surface of revolution with twice-differentiable sweeping rule function are shown to be sufficient for determining the axis except for certain singular configurations. Position and orientation error uncertainties and experimental results are presented for a cylindrical tactile sensor View full abstract»

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  • Inferring correlation between database queries: analysis of protein sequence patterns

    Page(s): 1030 - 1041
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    Given a subset P of a database, the problem of finding the query φ in a given database attribute having the closest extension to P is addressed. In the particular case that is outlined, P is the set of protein sequences in a protein sequence database matching a given protein sequence pattern, whereas φ is a query in the annotation of the database. Ideally, φ is the description of a biological function. If the extension of φ is very similar to P, an association between the pattern and the biological function described by the query may be inferred. An algorithm that efficiently searches the query space when negation is not considered is developed. Since the query language is a first-order language, the query space may be mapped into a set algebra in which a measure of stochastic dependence-an asymptotic approximation of the correlation coefficient-is used as a measure of set similarity. The algorithm uses the algebraic properties of such a measure to reduce the time required to search the query space. A prototype implementation of the algorithm has been tested in different collections of protein sequence patterns View full abstract»

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  • Active stereo: integrating disparity, vergence, focus, aperture and calibration for surface estimation

    Page(s): 1007 - 1029
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2568 KB)  

    An approach to integrating stereo disparity, camera vergence, and lens focus to exploit their complementary strengths and weaknesses through active control of camera focus and orientations is presented. In addition, the aperture and zoom settings of the cameras are controlled. The result is an active vision system that dynamically and cooperatively interleaves image acquisition with surface estimation. A dense composite map of a single contiguous surface is synthesized by automatically scanning the surface and combining estimates of adjacent, local surface patches. This problem is formulated as one of minimizing a pair of objective functions. The first such function is concerned with the selection of a target for fixation. The second objective function guides the surface estimation process in the vicinity of the fixation point. Calibration parameters of the cameras are treated as variables during optimization, thus making camera calibration an integral, flexible component of surface estimation. An implementation of this method is described, and a performance evaluation of the system is presented. An average absolute error of less than 0.15% in estimated depth was achieved for a large surface having a depth of approximately 2 m View full abstract»

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