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Pattern Analysis and Machine Intelligence, IEEE Transactions on

Issue 4 • Date Apr 1998

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Displaying Results 1 - 11 of 11
  • Incremental arc segmentation algorithm and its evaluation

    Publication Year: 1998 , Page(s): 424 - 431
    Cited by:  Papers (17)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (300 KB)  

    We present an incremental arc segmentation algorithm, which recovers the vectorized arc fragments obtained by the vectorization of a piece of arc image in a stepwise fashion. Due to proper threshold selection and consistent checking of cocircularity of the assumed arc pieces, the algorithm accurately constructs arcs from the vector input. Nearly 200 synthetic arcs, ranging in radius from five to 50 pixels, in open angle from 1/8π to 2π, and in thickness from one to nine pixels, are used in the experiments and evaluation. Parts of six real drawings, containing about 200 arcs, are also processed. The algorithm works well for arc segments greater than 10 pixels in radius, π/4 in angle, and one pixel in width View full abstract»

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  • Singularities and regularities on line pictures via symmetrical trapezoids

    Publication Year: 1998 , Page(s): 391 - 395
    Cited by:  Papers (7)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (172 KB)  

    An algorithm that decomposes a line image into singular and regular regions is presented. We define a contour trapezoid as the building block of regular regions, and postulate a maximal trapezoid set as the core of regular regions. Then, we describe an algorithm that calculates a maximal trapezoid set of a polygon and show how to use it to find a skeleton of a polygonal approximation of a contour. Experiments are explained to show the behavior of the new concept on real images as compared to previous algorithms View full abstract»

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  • Decision rule for pattern classification by integrating interval feature values

    Publication Year: 1998 , Page(s): 440 - 448
    Cited by:  Papers (5)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (452 KB)  

    Pattern classification based on Bayesian statistical decision theory needs a complete knowledge of the probability laws to perform the classification. In the actual pattern classification, however, it is generally impossible to get the complete knowledge as constant feature values are influenced by noise. Therefore, it is necessary to construct more flexible and robust theory for pattern classification. In this paper, a pattern classification theory using feature values defined on closed interval is formalized in the framework of Dempster-Shafer measure. Then, in order to make up the lack of information, an integration algorithm is proposed, which integrates the information observed by several information sources with considering source values View full abstract»

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  • Detection of text regions from digital engineering drawings

    Publication Year: 1998 , Page(s): 431 - 439
    Cited by:  Papers (12)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (268 KB)  

    An algorithm for text/graphics separation is presented in this paper. The basic principle of the algorithm is to erase nontext regions from mixed text and graphics engineering drawings, rather than extract text regions directly. This algorithm can be used to extract both Chinese and Western characters, dimensions, and symbols and has few limitations on the kind of engineering drawings and noise level. It is robust to text-graphics touching, text fonts, and written orientations View full abstract»

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  • Synchronous random fields and image restoration

    Publication Year: 1998 , Page(s): 380 - 390
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (588 KB)  

    We propose a general synchronous model of lattice random fields which could be used similarly to Gibbs distributions in a Bayesian framework for image analysis, leading to algorithms ideally designed for an implementation on massively parallel hardware. After a theoretical description of the model, we give an experimental illustration in the context of image restoration View full abstract»

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  • Ordinal measures for image correspondence

    Publication Year: 1998 , Page(s): 415 - 423
    Cited by:  Papers (113)  |  Patents (24)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3124 KB)  

    We present ordinal measures of association for image correspondence in the context of stereo. Linear correspondence measures like correlation and the sum of squared difference between intensity distributions are known to be fragile. Ordinal measures which are based on relative ordering of intensity values in windows-rank permutations-have demonstrable robustness. By using distance metrics between two rank permutations, ordinal measures are defined. These measures are independent of absolute intensity scale and invariant to monotone transformations of intensity values like gamma variation between images. We have developed simple algorithms for their efficient implementation. Experiments suggest the superiority of ordinal measures over existing techniques under nonideal conditions. These measures serve as a general tool for image matching that are applicable to other vision problems such as motion estimation and texture-based image retrieval View full abstract»

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  • Robust reweighted MAP motion estimation

    Publication Year: 1998 , Page(s): 353 - 365
    Cited by:  Papers (8)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (864 KB)  

    This paper proposes a motion estimation algorithm that is robust to motion discontinuity and noise. The proposed algorithm is constructed by embedding the least median squares (LMedS) of robust statistics into the maximum a posteriori (MAP) estimator. Difficulties in accurate estimation of the motion field arise from the smoothness constraint and the sensitivity to noise. To cope robustly with these problems, a median operator and the concept of reweighted least squares (RLS) are applied to the MAP motion estimator, resulting in the reweighted robust MAP (RRMAP). The proposed RRMAP motion estimation algorithm is also generalized for multiple image frame cases. Computer simulation with various synthetic image sequences shows that the proposed algorithm reduces errors, compared to three existing robust motion estimation algorithms that are based on M-estimation, total least squares (TLS), and Hough transform. It is also observed that the proposed algorithm is statistically efficient and robust to additive Gaussian noise and impulse noise. Furthermore, the proposed algorithm yields reasonable performance for real image sequences View full abstract»

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  • A pixel dissimilarity measure that is insensitive to image sampling

    Publication Year: 1998 , Page(s): 401 - 406
    Cited by:  Papers (163)  |  Patents (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (492 KB)  

    Because of image sampling, traditional measures of pixel dissimilarity can assign a large value to two corresponding pixels in a stereo pair, even in the absence of noise and other degrading effects. We propose a measure of dissimilarity that is provably insensitive to sampling because it uses the linearly interpolated intensity functions surrounding the pixels. Experiments on real images show that our measure alleviates the problem of sampling with little additional computational overhead View full abstract»

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  • Fast chain coding of region boundaries

    Publication Year: 1998 , Page(s): 407 - 415
    Cited by:  Papers (18)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (508 KB)  

    A fast single-pass algorithm to convert a multivalued image from a raster-based representation into chain codes is presented. All chain codes are obtained in linear time with respect to the number of chain segments that are generated at each raster according to a set of templates. A formal statement and the complexity and performance analysis of the algorithm are given View full abstract»

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  • The Hough transform versus the UpWrite

    Publication Year: 1998 , Page(s): 396 - 400
    Cited by:  Papers (12)  |  Patents (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (552 KB)  

    This paper compares the Hough transform and the UpWrite for the detection of lines, circles, and ellipses. Both ideal and noisy images are tested. The UpWrite is found to be more robust for images containing perturbation noise. For ideal images and images with speckle noise, the results are found to depend on the complexity of the object being detected, with more complex objects favoring the UpWrite View full abstract»

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  • Error guided design of a 3D vision system

    Publication Year: 1998 , Page(s): 366 - 379
    Cited by:  Papers (6)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (456 KB)  

    We argue that for a method to be useful in practice, it is necessary to perform its sensitivity analysis and to investigate its robustness to measurement errors. We present here a complete sensitivity analysis of the 3D reconstruction method based on projective geometry. We use this sensitivity analysis to best design a system for the inference of the shape of a block of granite from cameras placed at 90 degrees angular separation. The system has been tested on both real and synthetic data 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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Editor-in-Chief
David A. Forsyth
University of Illinois