A genetic algorithm for affine invariant object shape recognition

Author(s):  
P.W.M. Tsang
Author(s):  
P W M Tsang

In this paper, a novel technique for matching images of object shapes which have been subject to affine transformation caused by variations in the camera position is reported. The method is based on the genetic algorithm, and is more efficient and reliable than conventional approaches that rely on corresponding dominant point pairs to determine the best alignment between object boundaries. Experimental results are presented to demonstrate the feasibility of the approach and its capability in identifying object shapes that had been distorted with heavy noise contamination


Author(s):  
MICHIEL HAGEDOORN ◽  
REMCO C. VELTKAMP

Affine invariant pattern metrics are useful for shape recognition. It is important that such a metric is robust for various defects. We formalize these types of robustness using four axioms. Then, we present the reflection metric. This is an affine invariant metric defined for the large family of "boundary patterns". A boundary pattern is a finite union of n-1 dimensional algebraic surface patches in ℝn. Such a pattern may have multiple connected components. We prove that the reflection metric satisfies the four robustness axioms.


2015 ◽  
Vol 8 (5) ◽  
pp. 953-956 ◽  
Author(s):  
Sebo Uithol ◽  
Michele Franca ◽  
Katrin Heimann ◽  
Daniele Marzoli ◽  
Paolo Capotosto ◽  
...  

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