Heuristic strategy for feature matching in parallel curve detection

W. H. Wong; Horace H S Ip

doi:10.1109/ICSMC.1995.538463

Heuristic strategy for feature matching in parallel curve detection

W. H. Wong
, Horace H S Ip

City University of Hong Kong

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

2 Citations (Scopus)

Abstract

Feature matching has been proved very efficient as an approach for curve matching. However, when there are lots of features detected in the two curves, the possible combinations of matching among these features are prohibitive computationally. In this paper, we propose a heuristic algorithm to select the most promising coupling schemes out of these possible patterns. For parallel curve detection, the rationales we employed include proximity measure and compatibility between tangent orientations at these feature points.

Original language	English
Pages (from-to)	4273-4278
Journal	Proceedings of the IEEE International Conference on Systems, Man and Cybernetics
Volume	5
DOIs	https://doi.org/10.1109/ICSMC.1995.538463
Publication status	Published - 1995
Event	Proceedings of the 1995 IEEE International Conference on Systems, Man and Cybernetics. Part 2 (of 5) - Vancouver, BC, Can Duration: 22 Oct 1995 → 25 Oct 1995

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abstract = "Feature matching has been proved very efficient as an approach for curve matching. However, when there are lots of features detected in the two curves, the possible combinations of matching among these features are prohibitive computationally. In this paper, we propose a heuristic algorithm to select the most promising coupling schemes out of these possible patterns. For parallel curve detection, the rationales we employed include proximity measure and compatibility between tangent orientations at these feature points.",

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AU - Ip, Horace H S

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AB - Feature matching has been proved very efficient as an approach for curve matching. However, when there are lots of features detected in the two curves, the possible combinations of matching among these features are prohibitive computationally. In this paper, we propose a heuristic algorithm to select the most promising coupling schemes out of these possible patterns. For parallel curve detection, the rationales we employed include proximity measure and compatibility between tangent orientations at these feature points.

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U2 - 10.1109/ICSMC.1995.538463

DO - 10.1109/ICSMC.1995.538463

M3 - RGC 21 - Publication in refereed journal

SN - 0884-3627

VL - 5

SP - 4273

EP - 4278

JO - Proceedings of the IEEE International Conference on Systems, Man and Cybernetics

JF - Proceedings of the IEEE International Conference on Systems, Man and Cybernetics

T2 - Proceedings of the 1995 IEEE International Conference on Systems, Man and Cybernetics. Part 2 (of 5)

Y2 - 22 October 1995 through 25 October 1995

ER -

Heuristic strategy for feature matching in parallel curve detection

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