IEEE Transactions on Pattern Analysis and Machine Intelligence

This paper deals with the Bayesian method of choosing the best model for a given one-dimensional series among a finite number of candidates belonging to autoregressive (AR), moving average (MA), ARMA, and other families. The series could be either a sequence of observations in time as in speech applications, or a sequence of pixel intensities of a two-dimensional image. The observation set is not ... View full abstract»

A technique is presented for feature extraction of a waveform y based on its Tauberian approximation, that is, on the approximation of y by a linear combination of appropriately delayed versions of a single basis function x, i.e., y(t) = ΣM i = 1 aIx(t - τI), where the coefficients aI and the delays τI are ad... View full abstract»

This paper examines the amplitude fluctuations of band-limited functions with bounded zeroth absolute moments, and the problems associated with estimating the level crossing profiles of these functions. Level crossings have received increased attention as features for pattern recognition because of their capability to provide information related to both amplitude and frequency behavior. A detailed... View full abstract»

A method for efficiently generating a rational model of a wide-sense stationary time series is presented. In this method the autoregressive parameters associated with an ARMA model consisting of q zeros and p poles are optimally chosen with the selection being based on a finite set of time series observations. This selection is made so that a set of Yule-Walker equation approximations are ``best''... View full abstract»

This correspondence is concerned with adaptive digital processing to extract impulse-like signal features from the correlated background noise for detection of intruders with the seismic sensor data. Both the adaptive digital filtering and the adaptive Kalman filtering methods are developed and shown to perform nearly the same for a short data segment. For continued processing of a long duration s... View full abstract»

A nonlinear adaptive method is presented for filtering a signal which is corrupted by spikes which take discrete values Mi with probability Pi at random points in time. An unsupervised learning technique is used to estimate the unknown parameters Mi, Pi, and oi. The spikes are then removed using a Bayes classifier. A theoretical and experimental comparison with the MMSE linear filter is presented. View full abstract»

The nearest-neighbor decision rule for syntactic patterns is applied to seismic pattern classification. Each pattern is represented by a string. The string-to-string distance is used as a similarity measure. Another method using finite-state grammars inferred from the training samples and error-correcting parsers is also implemented. Both methods show equal recognition accuracy; however, the neare... View full abstract»

The restoration of images degraded by an additive white noise is performed by nonlinearly filtering a noisy image. The standard Wiener approach to this problem is modified to take into account the edge information of the image. Various filters of increasing complexity are derived. Experimental results are shown and compared to the standard Wiener filter results and other earlier attempts involving... View full abstract»

It is shown that a digital region is convex if and only if every pair of points in the region is connected by a digital straight line segment contained in the region. The midpoint property is shown to be a necessary but not a sufficient condition for the convexity of digital regions. However, it is shown that a digital region is convex if and only if it has the median-point property. View full abstract»

Consider the basic discrimination problem based on a sample of size n drawn from the distribution of (X, Y) on the Borel sets of Rdx {0, 1}. If 0 ⩽ R*. n → 0 is an arbitrary positive sequence, then for any discrimination rule one can find a distribution for (X, Y), not depending upon n, with Bayes probability of erro... View full abstract»

Standard image processing techniques which are used to enhance noncoherent optically produced images are not applicable to radar images due to the coherent nature of the radar imaging process. A model for the radar imaging process is derived in this paper and a method for smoothing noisy radar images is also presented. The imaging model shows that the radar image is corrupted by multiplicative noi... View full abstract»

This paper presents a suboptimal boundary estimation algorithm for noisy images which is based upon an optimal maximum likelihood problem formulation. Both the maximum likelihood formulation and the resulting algorithm are described in detail, and computational results are given. In addition, the potential power of the likelihood formulation is demonstrated through the presentation of three simple... View full abstract»

A structural analysis system for describing natural textures is introduced. The analyzer automatically extracts the texture elements in an input image, measures their properties, classifies them into some distinctive classes (one ``ground'' class and some ``figure'' classes), and computes the distributions of the gray level, the shape, and the placement of the texture elements in each class. These... View full abstract»

The alpha-beta algorithm for searching decision trees is adapted to allow parallel activity in different parts of a tree during the search. The algorithm has been implemented in a procedural simulation language (GASP IV). The simulation environment provides the illusion of multiple software processes and multiple hardware processors. A number of preliminary experiments have been done to gather sta... View full abstract»

The ``index of fuzziness'' and ``entropy'' of an image reflect a kind of quantitative measure of its enhancement quality. Their values are found to decrease with enhancement of an image when different sets of S-type membership functions with appropriate crossover points were considered for extracting the fuzzy property plane from the spatial domain of the image. View full abstract»

This correspondence defines approaches for the efficient generation of a spiral-like search pattern within bounded rectangularly tessellated regions. The defined spiral-like search pattern grows outward from a given source in a two-dimensional space, thus tending to minimize search time in many sequential tracking tasks. Efficient spiral generation is achieved by minimizing the number of operation... View full abstract»

The problem of estimating the error probability of a given classification system is considered. Statistical properties of the empirical error count (C) and the average conditional error (R) estimators are studied. It is shown that in the large sample case the R estimator is unbiased and its variance is less than that of the C estimator. In contrast to conventional methods of Bayes error estimation... View full abstract»

This correspondence describes a microcomputer system, called μBE (for microprocessor-based English), for processing natural languages. Its techniques and facilities, however, should be extendible to other languages. By using the microprocessor as special purpose hardware for several functions of a natural language processor (in particular, hashing and parsing), the system aids computationa... View full abstract»