Showing papers in "Pattern Recognition in 1995"

TL;DR: A new image thresholding method based on minimizing the measures of fuzziness of an input image and a fuzzy range is defined to find the adequate threshold value within this range.

TL;DR: Methods of optimization to derive the maximum likelihood estimates as well as the practical usefulness of these models are discussed and an application on stellar data which dramatically illustrated the relevance of allowing clusters to have different volumes is illustrated.

TL;DR: A reliable method for extracting structural features from fingerprint images is presented and a “goodness index” (GI) which compares the results of automatic extraction with manually extracted ground truth is evaluated.

TL;DR: Robust and time-efficient skeletonization of a (planar) shape can be achieved by first regularizing the Voronoi diagram of a shape's boundary points and then by establishing a hierarchic organization of skeleton constituents.

TL;DR: The purpose of this paper is to present and discuss the different ways to build a fuzzy mathematical morphology, and compare their properties with respect to mathematical morphology and to fuzzy sets and interpret them in terms of logic and decision theory.

TL;DR: Two methods for automatically locating text in complex color images that computes the local spatial variation in the gray-scale image, and locates text in regions with high variance are presented.

TL;DR: A new algorithm for solving the problem of clustering m objects into c clusters based on a tabu search technique is developed that compares favorably with both the k-means and the simulated annealing algorithms.

TL;DR: Recursion algorithms for fast computation of Legendre and Zernike moments of a grey-level image intensity distribution are presented and the recursive formulae can also be used in inverse moment transforms to reconstruct the original image from moments.

TL;DR: Through the use of a global geometric symmetry, a fast ellipse/circle detector is proposed in this paper, which significantly reduces the time required to evaluate all possible parameters without using edge direction information.

TL;DR: An overview of the character segmentation techniques in machine-printed documents is presented, which will cover techniques for segmenting uniformed or proportional fonts, broken and touching characters; techniques based on text image features and techniquesbased on recognition results.

TL;DR: Experimental results based on 496 signatures from 31 subjects are presented which show that HMM technique is very potential for signature verification.

TL;DR: A method for the off-line recognition of cursive handwriting based on hidden Markov models (HMMs) is described, which has an average correct recognition rate of over 98% on the word level and in experiments with cooperative writers using two dictionaries of I50 words each.

TL;DR: Systematic comparison shows that the new set of 16 features based on the statistics of geometrical attributes of connected regions in a sequence of binary images obtained from a texture image achieves a higher correct classification rate than the well-known Statistical Gray Level Dependence Matrix method, the recently proposed Statistical Feature Matrix, and Liu's features.

TL;DR: A novel set of shape descriptors that represents a digitized pattern in a concise way and that is particularly well-suited for the recognition of handprinted characters that are derived from the wavelet transform of a pattern's contour.

TL;DR: Experimental results on a large set of data show the efficiency and robustness of the proposed multiple experts system using neural networks.

TL;DR: In this article, a combination of self-organizing maps (SOMs) and fuzzy rules is used to classify handwritten numerals using a classifier and a fuzzy rule based classifier.

TL;DR: Several techniques for template matching by means of cross-correlation are reviewed and compared on a common task: locating eyes in a database of faces and approximation networks are introduced in an attempt to improve filter design by the introduction of nonlinearity.

TL;DR: A syntactic pattern recognition method of electrocardiograms (ECG) is described in which attributed automata are used to execute the analysis of ECG signals.

TL;DR: The problem of computing a constrained editing distance between ordered labeled trees, which can be applied to pattern recognition, syntactic tree comparison, classification tree comparison and other applications, is considered.

TL;DR: The technique of {\em modal matching}, an information-preserving shape decomposition for matching, describing, and comparing shapes despite sensor variations and nonrigid deformations, is employed for shape comparison in 2-D image databases.

TL;DR: A fast digital Radon transform based on recursively defined digital straight lines is described, which has the sequential complexity of N^2 log N additions for an N x N image and is shown to be quite similar to the FFT algorithm for decimation in frequency.

TL;DR: This work describes this matching problem in terms of cost minimization and presents an algorithm to approach the minimal cost mapping using simulated annealing, a random rearrangement scheme to alter the mapping towards the optimal mapping.

TL;DR: A simple and efficient algorithm using the maxima tracking approach on Euclidean distance transform to detect skeleton points is presented and can be modified to eliminate non-significant short skeletal branches originating from the object contour while the critical shape-informative medial axes are preserved.

TL;DR: A divisive clustering algorithm which makes use of both similarity and dissimilarity is proposed and the results obtained are compared with other methods.

TL;DR: The current model and algorithm are more accurate, yet substantially simpler, than earlier versions of this approach, and are tested on photographs of real-world surfaces.

TL;DR: A new method for modeling and recognizing cursive words with hidden Markov models (HMM) is presented, using a sequence of thin fixed-width vertical frames that capture the local features of the handwriting.

TL;DR: A normalized correlation method is used for the preparation of montages when there is no rotational shift between neighboring images, and a pyramidal approach is developed to reduce the computation.

TL;DR: This paper considers the use of radial basis functions for modelling the non-linear transformation of a data set obtained by a multidimensional scaling analysis and a scheme based on iterative majorization is proposed for obtaining the parameters of the network.

TL;DR: This work presents a method for integrating the high frequncy information from the shape from shading and the low frequency information from stereo, and results obtained with a variety of synthetic and real images are discussed.

TL;DR: The extent to which principal components, Sammon's algorithm and the extension of the self-organizing feature map (SOFM) preserve the MTP property is discussed and the first two methods preserve distance ranks on seven data sets much more effectively than extended SOFM.