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On curve matching

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TLDR
Two algorithms to find the longest common subcurve of two 2D curves are presented, based on conversion of the curves into shape signature strings and application of string matching techniques to find long matching substrings, followed by direct curve matching of the corresponding candidate subcurves to finding the longest matching subCurve.
Abstract
Two algorithms to find the longest common subcurve of two 2D curves are presented. These algorithms are based on conversion of the curves into shape signature strings and application of string matching techniques to find long matching substrings, followed by direct curve matching of the corresponding candidate subcurves to find the longest matching subcurve. The first algorithm is of complexity O(n), where n is the number of sample points on the curves. The second one, while being theoretically somewhat less efficient, proved to be robust and efficient in practical applications. Both algorithms solve the problem of general curves without being dependent on some set of special points on the curves. The algorithms have industrial applications to problems of object assembly and object recognition. Experimental results are included. The algorithms can be easily extended to the 3D case. >

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Citations
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Journal ArticleDOI

Iterative point matching for registration of free-form curves and surfaces

TL;DR: A heuristic method has been developed for registering two sets of 3-D curves obtained by using an edge-based stereo system, or two dense3-D maps obtained by use a correlation-based stereoscopic system, and it is efficient and robust, and yields an accurate motion estimate.

Iterative point matching for registration of free-form curves

TL;DR: In this article, a least-squares technique is used to estimate 3D motion from the point correspondences, which reduces the average distance between curves in two sets, and yields an accurate motion estimate.
Journal ArticleDOI

An efficiently computable metric for comparing polygonal shapes

TL;DR: A method for comparing polygons that is a metric, invariant under translation, rotation, and change of scale, reasonably easy to compute, and intuitive is presented.
Proceedings ArticleDOI

Recognition of Shapes by Editing Shock Graphs

TL;DR: The effectiveness of the proposed technique in the presence of a variety of visual transformations including occlusion, articulation and deformation of parts, shadow and highlights, viewpoint variation, and boundary perturbations is demonstrated.
Journal ArticleDOI

Recovering the position and orientation of free-form objects from image contours using 3D distance maps

TL;DR: In this paper, a least squares minimization of the energy necessary to bring the set of the camera-contour projection lines tangent to the surface is proposed to solve the 3D/2D matching problem.
References
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Proceedings ArticleDOI

Linear pattern matching algorithms

Peter Weiner
TL;DR: A linear time algorithm for obtaining a compacted version of a bi-tree associated with a given string is presented and indicated how to solve several pattern matching problems, including some from [4] in linear time.
Journal ArticleDOI

A Space-Economical Suffix Tree Construction Algorithm

TL;DR: A new algorithm is presented for constructing auxiliary digital search trees to aid in exact-match substring searching that has the same asymptotic running time bound as previously published algorithms, but is more economical in space.
Journal ArticleDOI

HYPER: A New Approach for the Recognition and Positioning of Two-Dimensional Objects

TL;DR: The method has been integrated within a vision system coupled to an indutrial robot arm, to provide automatic picking and repositioning of partially overlapping industrial parts to provide strong robustness to partial occlusions.
Journal ArticleDOI

Euclidean shortest paths in the presence of rectilinear barriers

TL;DR: The goal is to find interesting cases for which the solution can be obtained without the explicit construction of the entire visibility graph, which solve the problems by constructing the shortest-path tree from the source to all the vertices of the obstacles and to the destination.
Journal ArticleDOI

Identification of partially obscured objects in two and three dimensions by matching noisy characteristic

TL;DR: Efficient methods for smoothing the noisy data and for matching portions of the observed object boundaries (or of characteristic curves lying on bounding surfaces of 3-D objects) to prestored models are described.
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