Showing papers in "Pattern Recognition in 1981"

TL;DR: This survey summarizes some of the proposed segmentation techniques in the area of biomedical image segmentation, which fall into the categories of characteristic feature thresholding or clustering and edge detection.

TL;DR: It is shown that in the context of multivariate statistical analysis and statistical pattern recognition the three transforms are very similar if a specific estimate of the column covariance matrix is used.

TL;DR: The Hough transform was improved by O'Gorman and Clowes by taking into account the gradient direction and the resulting scatter of the peaks can be reduced by using a weighting function in the transform.

TL;DR: Analysis of the difficulties that confront existing thinning algorithms results in a new, systematic approach to thinning, leading to a family of algorithms able to achieve guaranteed standards of skeleton precision.

TL;DR: Improved techniques for automatic recognition of human face profiles are reported, each face description being a 17-dimensional feature vector whose components were formed from the averages of three sittings.

TL;DR: It is shown that many known algorithms of clustering and pattern recognition can be characterized as efforts to minimize entropy, when suitably defined.

TL;DR: It is shown how a theorem in plane geometry can be converted into a O(n log n) algorithm for decomposing a polygon into star-shaped subsets, which contrasts with the heavy computational burden of existing methods.

TL;DR: An algorithm for determining the position of a robot from only one TV image has been developed by transforming the standard square pattern of the input image into its skeleton by applying the method of least squares.

TL;DR: There is a trade-off between asymptotic performance and sample deletion which can adversely affect the finite sample performance and a kk' rule is proposed to minimize the proportion of deleted samples.

TL;DR: A technique for the automatic recognition of printed Farsi texts is presented and its steps are discussed as follows: digitization, editing, line separation, subword separation, symbol separation, recognition, and postprocessing.

TL;DR: Experimental results based on both simulated and real multispectral remote sensing data demonstrate the effectiveness of the contextual classifier.

TL;DR: An algorithm which transforms a digital figure into a set of 8-simple digital arcs and curves, by employing local sequential operations, is illustrated and the notion of local elongation is employed to find those contour regions which can be regarded as significant protrusions.

TL;DR: This paper describes an interactive system which uses a decision surface modeling approach to solve the first case and uses clustering techniques in the three-dimensional color space to solved the second case.

TL;DR: Two distinct approaches to image-segmentation are described, both of which take the form of so-called region-growing algorithms, which are based on a binary relation named relative similarity relation which reflects relative properties in an image.

TL;DR: The objective of this paper is the automatic identification of individual persons by means of their handwriting images, digitized by a computer-controlled TV-camera, which provides features representing global statistical information about the image.

TL;DR: An on-line recognition method for hand-written characters utilizing stroke vector sequences and a positional vector sequence has been developed and the similarity of two shapes and the complexity of a stroke have been introduced to reduce the dictionary size and the processing time.

TL;DR: This paper describes a technique to transform a two-dimensional shape into a generalized fuzzy binary relation whose clusters represent the meaningful simple parts of the shape, and uses this procedure on touching chromosomes defining the simple parts to be the separated chromosomes.

TL;DR: In this paper, the authors use filtered x and y projections to determine possible positions of corners, so that corner detection can be applied only in the vicinity of these positions, even in cases where the object would be hard to segment (unimodal histogram).

TL;DR: This paper illustrates that a combination of these two methods may reinforce the discriminating power of a system for the recognition of characters by making use of Fourier shape descriptors and contour approximations.

TL;DR: An operational automatic system is presented that measures height and smallest rectangular hull of the vertical projection for parcels or suitcases on a conveyor belt and speed and accuracy performance for different object shapes are discussed.

TL;DR: An efficient algorithm for subgraph isomorphism that combines tree search with relaxation by using resolution is presented and can be easily modified to apply to multi-relation labeled graphs, attributed graphs and some higher order structures such as arrangements.

TL;DR: The Bayes population assignment of x and Tx are shown to be equivalent for a compression matrix T explicitly calculated as a function of the means and covariances of the given populations.

TL;DR: The efficient use of MPP for various types of image processing operations, including point and local operations, discrete transforms and computation of image statistics is described.

TL;DR: The main objective of this notation is the simplification of some mathematical and geometrical processes in this analysis of shapes and surfaces.

TL;DR: The design of a fast, flexible and dynamically microprogrammable pipelined image processor is presented, especially suited to perform local operations of both logical and arithmetic character on pictures, stored in a random access image memory in a 256 level grey scale.

TL;DR: Progress towards generating a representation of the drawing as a set of line segments and interpreted characters is described, within an overall strategy for planning the sampling of the image and the application of analysis algorithms.

TL;DR: Two examples are given of the state-of-the-art of pattern recognition as regards the analysis of images of human and animal tissue: the counting of cell nuclei of normal and abnormal rabbit kidney and the detection of boundaries of endothelial cells of the living human cornea.

TL;DR: Techniques highlighted include: isodensity contour tracing, geometrical boundary repair, heuristic search, regional pre-processing, Hough transforms, and general parallel edge finding algorithms.

TL;DR: Smoothing parallel to the image contours followed by a Laplace filter produces the best results with regard to centromere finding, but at the expense of fragmenting a greater proportion of chromosome images than the other techniques.

TL;DR: A fast boundary finding algorithm is presented which works without threshold operation and without any interactive control and can be easily adapted to other problems by modification of a set of parameters.