Showing papers in "Pattern Recognition in 1978"

TL;DR: An application of symmetric axis geometry to shape classification and description, in which a sequential string of features is derived, and a weighting measure is developed which evaluates the importance of these shape descriptors.

TL;DR: A method for determining the mutual nearest neighbours (MNN) and mutual neighbourhood value (mnv) of a sample point, using the conventional nearest neighbours, is suggested.

TL;DR: This paper discusses a method of point pattern matching that can define a figure of merit for δij according to how closely other point pairs coincide underδij, and its possible advantages relative to other methods are discussed.

TL;DR: An adaptive quantization scheme, based on histogram peak sharpening, was applied to two of the images; the results do not seem to be as good as those obtained using variable thresholding.

TL;DR: “Smooth” modification of the counting estimator, or sample success proportion, is recommended to reduce bias and variance while retaining robustness, and the “bootstrap” method of Efron can approximately correct an additive estimator's bias using an ancillary computer simulation.

TL;DR: A tutorial survey of techniques for using contextual information in pattern recognition is presented, with emphasis on the problems of image classification and text recognition, where the text is in the form of machine and handprinted characters, cursive script, and speech.

TL;DR: In this article, the authors consider the classification problem in the context of two equiprobable multivariate Gaussian densities with a common covariance matrix and provide expressions which relate p opt to the number of available training samples and the Mahalanobis distance between the two populations.

TL;DR: Applications of iterative methods in image analysis, which include histogram modification, noise cleaning, edge and curve detection, thinning, angle detection, template matching, and region labelling, are described.

TL;DR: Hough-like transforms may be used to detect curves in digital pictures using essentially parallel character of transforms and Elements of theory are presented for performance prediction together with simulated results.

TL;DR: “ 효과 차이가 존재하는 것으로 구분하여’, 팝아트 작품은 기능지향 브랜드콘셉

TL;DR: Computer recognition of machine-printed letters of the Tamil alphabet is described, with agreement the letters are recognized and printed out in Roman letters following a special method of transliteration.

TL;DR: Human face profiles are automatically recognized by computer processes and absolute recognition accuracy ranges from 86 to nearly 100% under various conditions for a population of 121 persons having 3 poses each on file.

TL;DR: The ambiguity problem resulting in picture reconstruction from projection sets is described and a technique is developed that addresses itself first to unambiguous areas of the picture in reconstruction.

TL;DR: A digital computer based technique for the selection of optimum test frequencies for fault diagnosis of analogue systems is presented and is found to correlate well with the actual diagnosability of faults for a simulation of varying fault levels and including varying production tolerances for the non-faulty components.

TL;DR: The feature definition procedure which is proposed involves partitioning a large set of highly correlated features into subsets, or clusters, through hierarchical clustering and reducing the original set of correlated features to a small set of nearly uncorrelated features.

TL;DR: The use of texture parameters in the differentiation of white blood cells is presented and four different methods of texture analysis were applied to a set of 160 cells from 3 different classes.

TL;DR: This paper contains a Monte Carlo study of the characteristics of the cophenetic correlation and a related measure of agreement which have been both interpreted in terms of generalized variance for some different hierarchical cluster algorithms.

TL;DR: It has been found that the temporal pattern of change in the spectral response of a crop constitutes its signature and provides a basis for crop classification.

TL;DR: It is shown that in the two-class case and when ties in voting are broken at random, the (2k′) and (2K′−1)-NN rules achieve identical large-sample performances.

TL;DR: An image segmentation technique is proposed which uses a texture measure that counts the number of local extrema in a window centered at each picture point to derive number of segments in which to divide the original image.

TL;DR: This work utilizes the concept of “Composite set” ( C -set) and of the related C -calculus to study some standard problems of pattern analysis and general processing of signals and the cases of nonconvergence are proved to be of some interest.

TL;DR: A multiple threshold perceptron which learns a particular type of piecewise linear discriminant set of functions, namely those that are describable by a set of parallel hyperplanes is defined.

TL;DR: It is observed that it is not possible to classify the fingerprint patterns in the absence of accurate registration of the fingerprint.

TL;DR: The methodology suggested in the paper provides a structural pattern recognition generalization to phrase-structured syntactic pattern recognition.

TL;DR: The robustness and real-time operation of the system are largely attributed to the preprocessing and stroke identification techniques developed, which include a new two-stage syntactic classifier for the identification of curvilinear strokes.

TL;DR: In this paper, the authors discuss the effects of gender stereotypes on women's reproductive health and gender diversity in the South Korean population, and propose a new approach for women's health.

TL;DR: This paper presents a simple and efficient clustering technique based on the partitioning of the data histogram, developed in the context of a study of possible unsupervized classification procedures for multispectral earth imagery.

TL;DR: The numerical results of the study and the direct viewing of the principal images show that three out of the seven have so much noise that they do not yield any useful information and only the first two principal images have excellent stability, and they contain most of the total contrast variance of the scene.

TL;DR: This paper describes an algorithm consisting of two parts; the first is a steepest-descent method for finding the best match in a given locale, and the second is a procedure for selecting starting points for the local search.

TL;DR: A novel method is presented to generate the surfaces in three dimensions using the algorithm for the maxmin problem using the nearest-neighbor rule decision surfaces.