COMPUTER VISION, GRAPHICS,AND IMAGE PROCESSING46, 138-139 (1989)
Abstracts of Papers Accepted for Publication PAPERS Characteristics of edNLC-Graph Grammar for Syntactic Pattern Recognition. MARIUSZ FLASIIqSKI. Department of Computer Science, Jagiellonian University, Kracow, Poland. Received September 28, 1987; accepted November 21, 1988. An edNLC--graph grammar (introduced in Janssens and Rozenberg (Inform. Sci. 20, 1980, 191-216)) is a strong formalism for describing the scene. This grammar generates node- and edge-labelled graphs (EDG-graphs). The method of construction of unambiguous string EDG-graph representation is briefly described. The characteristics of edNLC-graph grammar for syntactic pattern recognition presented in this paper allows us to construct a deterministic syntax analyzer in a simple way.
An Analytic Solution for the Perspective 4-Point Problera. RADU HORAUD, BERNARD CONIO, AND OLIVIER LEBOULLEUX. LIFIA, 46 Avenue Fdix Viallet, 38031 Grenoble, France. BERNARDLACOLLE. TIM3, BP 68, 38402 Saint-Martin d'H~res, France. Received November 2, 1988; accepted December 13, 1988. The perspective n-point (PnP) problem is the problem of finding the position and orientation of a camera with respect to a scene object from n correspondence points. In this paper we propose an analytic solution for the perspective 4-point problem. The solution is found by replacing the four points with a pencil of three lines and by exploring the geometric constraints available with the perspective camera model. We show how the P4P problem is cast into the problem of solving a biquadratic polynomial equation in one unknown. Although developed as part of an object recognition from a single view system, the solution might well be used for hand-eye coordination, landmark-guided navigation, and for fast determination of exterior camera parameters in general.
Shape Matching Using CurvatureProcesses. EVANGELOSE. M/LOS. Department of Computer Science, University of Toronto, Toronto, Canada M5S 1A4. Received April 27, 1988; accepted December 13, 1988. Shape matching is a fundamental problem of vision in general, and of interpretation of deforming shapes in particular. The objective of matching in this instance is to recover the deformation and therefore generalizes the notion of correlation, which aims to only produce a numerical measure of the similarity between two shapes. To address shape matching, we introduce a new representation of a dosed 2D shape as a cyclic sequence of the extended circular images of the convex and concave segments of its contour. This representation is then used to establish correspondences between segments of the two contours using dynamic programming. Finally, we compute a recovery of the differences between two similar contours in terms of the action of curvature processes. Computation of convex and concave segments of the contours, given in piecewise linear form, is accomplished using the analytic representation of a local B-spline fit. We show the result of our deformation recovery scheme applied to dynamic cloud silhouette analysis using hand-traced input from real satellite images.
Look-up Table Loadings for Image Processing with Controlled Knots. J . M . REBORDT,O. Laborat6rio Nacional de Engenharia e Tecnologia Industrial, Azinhaga dos Lameiros h Estrada do Paso de Lumiar, 1699 Lisboa, Codex, Portugal. Received December 12, 1988; accepted December 16, 1988. Look-up tables can be loaded with the values of transfer functions, in order to accomplish real time radiometric processing. Some algebraic families of nondecreasing functions with one or two parameters, 138 0734-189X/89 $3.00 Copyright 9 1989 by Academic Press, Inc. All rights of reproductionin any form reserved.
ABSTRACTS OF PAPERS ACCEPTED FOR PUBLICATION
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that make it easy to grasp the geometrical meaning, are presented. These functions can be easily loaded in the LUT's of digital image processors with a pipehne architecture allowing real time interactive processing. These functions can be used to build models for n-modal histograms, to adjust the radiometry of images to match prespecified statistics and to compensate nonhnearities of the photographic process, when digitizing aerial photography in a remote sensing facility. Some examples should help explaining how to develop other algebraic famihes suitable to specific applications.
NOTE Epicardial Surface Estimation .from Coronary Angiograms. A.A. YOUNG AND P. J. HUNTER. Department of Theoretical and Apphed Mechanics, School of Engineering, University of Auckland, Private Bag, Auckland, New Zealand. B. H. SMAILL. Department of Physiology, School of Medicine, University of Auckland, Private Bag, Auckland, New Zealand. Received August 23, 1988; accepted December 16, 1988. We describe a system for estimating the epicardial surface of the heart using data obtained from biplane coronary cindangiograms. The three-dimensional (3D) geometry of the left coronary arterial tree at an instant in time is interactively reconstructed as an ensemble of 3D Bdzier cubics. This provides a compact representation of the tree structure, incorporating the 3D location of the bifurcation points and their connectivity as well as the locii of the connecting vessels. A finite element model for the surface is defined using bicubic Hermite basis functions to interpolate prolate spheroidal geometric parameters. As the arteries are not uniformly distributed around the left ventricular epicardium, weighted spline-type smoothness constraints are incorporated into the error function along with the least squares error estimate. A trial fit to data describing the superficial arteries of an isolated dog heart was compared to a uniform and dense data set covering the entire epicardial surface obtained from the same heart. Good agreement was found in elements containing coronary data, with the error increasing in a controlled manner in the remaining elements. Results with angiographic data are also given. The model is readily extended to fit time-varying surfaces with the inclusion of a time basis function and is intended for use in subsequent vessel tracking algorithms.
SURVEY Image Analysis and Computer Vision." 1988. AZRIEL ROSENFELD. Center for Automation Research, University of Maryland, College Park, Maryland 20742-3411. Received January 5, 1989. This paper presents a bibliography of over 1600 references related to computer vision and image analysis, arranged by subject matter. The topics covered include architectures; computational techniques; feature detection, segmentation, and image analysis; matching, stereo, and time-varying imagery; shape and geometry; color and texture; and 3-dimensional scene analysis. A few references are also given on related topics, such as comptuer graphics, image input/output, image processing, optical processing, neural nets, visual perception, pattern recognition, and artificial intelligence.