Partial shape matching using genetic algorithms

Authors:
Ender Ozcan;Chilukuri K. Mohan
Affiliations:
-;-
Venue:
Pattern Recognition Letters
Year:
1997

Citing 3
Cited 16

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Geometric matching of circular features by least squares fitting

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Matching Incomplete Objects Using Boundary Signatures

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A robust method for partial deformed fingerprints verification using genetic algorithm

Expert Systems with Applications: An International Journal
Enhanced affine invariant matching of broken boundaries based on particle swarm optimization and the dynamic migrant principle

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Affine invariant matching of broken boundaries based on simple genetic algorithm and contour reconstruction

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Partial matching of garment panel shapes with dynamic sketching design

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A genetic algorithm for generating improvised music

EA'07 Proceedings of the Evolution artificielle, 8th international conference on Artificial evolution
Affine invariant matching of broken boundaries in noisy images based on the quality migrant injection genetic algorithm and a successive erosion and distance accumulation scheme

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A Graphics Processing Unit Accelerated Genetic Algorithm for Affine Invariant Matching of Broken Contours

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Pre-organizing Shape Instances for Landmark-Based Shape Correspondence

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Fast affine invariant shape matching from 3d images based on the distance association map and the genetic algorithm

ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part IV

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Abstract

Shape recognition is a challenging task when images contain overlapping, noisy, occluded, partial shapes. This paper addresses the task of matching input shapes with model shapes described in terms of features such as line segments and angles. The quality of matching is gauged using a measure derived from attributed shape grammars. We apply genetic algorithms to the partial shape-matching task. Preliminary results, using model shapes with 6 to 70 features each, are extremely encouraging.