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Pattern Analysis and Machine Intelligence, IEEE Transactions on

Issue 6 • Date Jun 1994

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Displaying Results 1 - 13 of 13
  • On the generalization ability of neural network classifiers

    Publication Year: 1994 , Page(s): 659 - 663
    Cited by:  Papers (10)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (464 KB)  

    This correspondence presents a method for evaluation of artificial neural network (ANN) classifiers. In order to find the performance of the network over all possible input ranges, a probabilistic input model is defined. The expected error of the output over this input range is taken as a measure of generalization ability. Two essential elements for carrying out the proposed evaluation technique are estimation of the input probability density and numerical integration. A nonparametric method, which depends on the nearest M neighbors, is used to locally estimate the distribution around each training pattern. An orthogonalization procedure is utilized to determine the covariance matrices of local densities. A Monte Carlo method is used to perform the numerical integration. The proposed evaluation technique has been used to investigate the generalization ability of back propagation (BP), radial basis function (RBF) and probabilistic neural network (PNN) classifiers for three test problems View full abstract»

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  • A regularized contrast statistic for object boundary estimation-implementation and statistical evaluation

    Publication Year: 1994 , Page(s): 561 - 570
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1008 KB)  

    We propose an optimization approach to the estimation of a simple closed curve describing the boundary of an object represented in an image. The problem arises in a variety of applications, such as template matching schemes for medical image registration. A regularized optimization formulation with an objective function that measures the normalized image contrast between the inside and outside of a boundary is proposed. Numerical methods are developed to implement the approach, and a set of simulation studies are carried out to quantify statistical performance characteristics. One set of simulations models emission computed tomography (ECT) images; a second set considers images with a locally coherent noise pattern. In both cases, the error characteristics are found to be quite encouraging. The approach is highly automated, which offers some practical advantages over currently used technologies in the medical imaging field View full abstract»

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  • Digital planarity of rectangular surface segments

    Publication Year: 1994 , Page(s): 647 - 652
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (556 KB)  

    We generalize the concept of evenness which has been developed for digital straight lines. Evenness is a necessary and sufficient condition for a digital arc segment to be a digital straight line segment. We prove that evenness is also a necessary and sufficient condition for a rectangular surface segment to be a digital plane segment. This is not true for surface segments of arbitrary shape. To clarify the relation between shape and evenness we introduce the notion of a regular shape and of an arbitrarily extendable even set View full abstract»

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  • Recognition of handwritten cursive Arabic characters

    Publication Year: 1994 , Page(s): 664 - 672
    Cited by:  Papers (22)  |  Patents (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (892 KB)  

    An automatic off-line character recognition system for handwritten cursive Arabic characters is presented. A robust noise-independent algorithm is developed that yields skeletons that reflect the structural relationships of the character components. The character skeleton is converted to a tree structure suitable for recognition. A set of fuzzy constrained character graph models (FCCGM's), which tolerate large variability in writing, is designed. These models are graphs, with fuzzily labeled arcs used as prototypes for the characters. A set of rules is applied in sequence to match a character tree to an FCCGM. Arabic handwritings of four writers were used in the learning and testing stages. The system proved to be powerful in tolerance to variable writing, speed, and recognition rate View full abstract»

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  • Optimal structuring elements for the morphological pattern restoration of binary images

    Publication Year: 1994 , Page(s): 589 - 601
    Cited by:  Papers (9)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1260 KB)  

    In this paper, we derive the optimal structuring elements of morphological filters in image restoration. The expected pattern transformation of random sets is presented. An estimation theory framework for random sets is subsequently proposed. This framework is based on the least mean difference (LMD) estimator. The LMD estimator is defined to minimize the cardinality of the expected pattern transformation of the set-difference of the parameter and the estimate. Several important results for the determination of the LMD estimator are derived. The LMD structuring elements of morphological filters in image restoration are finally derived View full abstract»

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  • Shape matching using LAT and its application to handwritten numeral recognition

    Publication Year: 1994 , Page(s): 618 - 629
    Cited by:  Papers (22)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (988 KB)  

    This paper describes an iterative technique for gradually deforming a mask binary image with successive local affine transformation (LAT) operations so as to yield the best match to an input binary image as one new and promising approach toward robust handwritten character recognition. The method uses local shapes in the sense that the LAT of each point at one location is optimized using locations of other points by means of least-squares data fitting using Gaussian window functions. It also uses a multiscale refinement technique that decreases the spread of window functions with each iteration. Especially in handwritten character recognition, structural information is indispensable for robust shape matching or discrimination. The method is enhanced to explicitly incorporate structures by weighting the above least-squares criterion with similarity measures of both topological and geometric features of the mask and input images. Moreover, deformation constraints are imposed on each iteration, not only to promote and stabilize matching convergence but also to suppress an excessive matching process. Shape matching experiments have been successfully carried out using skeletons of totally unconstrained handwritten numerals View full abstract»

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  • Collision detection of a moving polygon in the presence of polygonal obstacles in the plane

    Publication Year: 1994 , Page(s): 571 - 580
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (796 KB)  

    This paper presents a new approach for the following collision detection problem in the plane: Let a simple polygon P rotate at a center &ogr; with constant angular velocity ω and translate towards a set of polygonal obstacles S with constant velocity ν. Given P and S as well as their initial positions, and given also the velocities of P, determine whether or not P will collide with any element of S and report the collided elements of S if collisions occurred. An O(mn) worst-case optimal algorithm is proposed to solve this problem, where n is the number of vertices of P and m is the number of vertices of the obstacles in S View full abstract»

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  • Seeded region growing

    Publication Year: 1994 , Page(s): 641 - 647
    Cited by:  Papers (343)  |  Patents (57)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1252 KB)  

    We present here a new algorithm for segmentation of intensity images which is robust, rapid, and free of tuning parameters. The method, however, requires the input of a number of seeds, either individual pixels or regions, which will control the formation of regions into which the image will be segmented. In this correspondence, we present the algorithm, discuss briefly its properties, and suggest two ways in which it can be employed, namely, by using manual seed selection or by automated procedures View full abstract»

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  • Bar code waveform recognition using peak locations

    Publication Year: 1994 , Page(s): 630 - 640
    Cited by:  Papers (21)  |  Patents (5)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (960 KB)  

    Traditionally, zero crossings of the second derivative provide edge features for the classification of blurred waveforms. The accuracy of these edge features deteriorates in the case of severely blurred images. In this paper, a new feature is presented that is more resistant to the blurring process, the image, and waveform peaks. In addition, an estimate of the standard deviation σ of the blurring kernel is used to perform minor deblurring of the waveform. Statistical pattern recognition is used to classify the peaks as bar code characters. The noise tolerance of this recognition algorithm is increased by using an adaptive, histogram-based technique to remove the noise. In a bar code environment that requires a misclassification rate of less than one in a million, the recognition algorithm showed a 43% performance improvement over current commercial bar code reading equipment View full abstract»

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  • Simulated annealing: a proof of convergence

    Publication Year: 1994 , Page(s): 652 - 656
    Cited by:  Papers (15)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (524 KB)  

    We prove the convergence of the simulated annealing procedure when the decision to change the current configuration is blind of the cost of the new configuration. In case of filtering binary images, the proof easily generalizes to other procedures, including that of Metropolis. We show that a function Q associated with the algorithm must be chosen as large as possible to provide a fast rate of convergence. The worst case (Q constant) is associated with the “blind” algorithm. On the other hand, an appropriate Q taking sufficiently high values yields a better rate of convergence than that of Metropolis procedure View full abstract»

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  • Algorithms for the decomposition of gray-scale morphological operations

    Publication Year: 1994 , Page(s): 581 - 588
    Cited by:  Papers (5)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (728 KB)  

    The choice and detailed design of structuring elements plays a pivotal role in the morphologic processing of images. A broad class of morphological operations can be expressed as an equivalent supremum of erosions by a minimal set of basis filters. Diverse morphological operations can then be expressed in a single, comparable framework. The set of basis filters are data-like structures, each filter representing one type of local change possible under that operation. The data-level description of the basis set is a natural starting point for the design of morphological filters. This paper promotes the use of the basis decomposition of gray-scale morphological operations to design and apply morphological filters. A constructive proof is given for the basis decomposition of general gray-scale morphological operations, as are practical algorithms to find all of the basis set members for these operations View full abstract»

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  • Document image decoding using Markov source models

    Publication Year: 1994 , Page(s): 602 - 617
    Cited by:  Papers (42)  |  Patents (57)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1476 KB)  

    Document image decoding (DID) is a communication theory approach to document image recognition. In DID, a document recognition problem is viewed as consisting of three elements: an image generator, a noisy channel and an image decoder. A document image generator is a Markov source (stochastic finite-state automaton) that combines a message source with an imager. The message source produces a string of symbols, or text, that contains the information to be transmitted. The imager is modeled as a finite-state transducer that converts the 1D message string into an ideal 2D bitmap. The channel transforms the ideal image into a noisy observed image. The decoder estimates the message, given the observed image, by finding the a posteriori most probable path through the combined source and channel models using a Viterbi-like dynamic programming algorithm. The proposed approach is illustrated on the problem of decoding scanned telephone yellow pages to extract names and numbers from the listings. A finite-state model for yellow page columns was constructed and used to decode a database of scanned column images containing about 1100 individual listings View full abstract»

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  • Openings can introduce zero crossings in boundary curvature

    Publication Year: 1994 , Page(s): 656 - 658
    Cited by:  Papers (6)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (248 KB)  

    Chen and Yan (1989) presented a result on zero crossings of boundary curvature under morphological openings. In this correspondence, it is shown, by means of a counter example, that this result is not correct. An analysis of the counter example shows where Chen and Yan go wrong and determines a class of images for which their theorem holds 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