DocumentCode :
1247817
Title :
Precision range image registration using a robust surface interpenetration measure and enhanced genetic algorithms
Author :
Silva, Luciano ; Bellon, Olga R P ; Boyer, Kim L.
Author_Institution :
Departamento de Informatica, Universidade Federal do Parana, Curitiba, Brazil
Volume :
27
Issue :
5
fYear :
2005
fDate :
5/1/2005 12:00:00 AM
Firstpage :
762
Lastpage :
776
Abstract :
This paper addresses the range image registration problem for views having low overlap and which may include substantial noise. The current state of the art in range image registration is best represented by the well-known iterative closest point (ICP) algorithm and numerous variations on it. Although this method is effective in many domains, it nevertheless suffers from two key limitations: it requires prealignment of the range surfaces to a reasonable starting point; and it is not robust to outliers arising either from noise or low surface overlap. This paper proposes a new approach that avoids these problems. To that end, there are two key, novel contributions in this work: a new, hybrid genetic algorithm (GA) technique, including hill climbing and parallel-migration, combined with a new, robust evaluation metric based on surface interpenetration. Up to now, interpenetration has been evaluated only qualitatively; we define the first quantitative measure for it. Because they search in a space of transformations, GA are capable of registering surfaces even when there is low overlap between them and without need for prealignment. The novel GA search algorithm we present offers much faster convergence than prior GA methods, while the new robust evaluation metric ensures more precise alignments, even in the presence of significant noise, than mean squared error or other well-known robust cost functions. The paper presents thorough experimental results to show the improvements realized by these two contributions.
Keywords :
genetic algorithms; image registration; iterative methods; stochastic processes; hybrid genetic algorithm technique; iterative closest point algorithm; mean squared error; precision range image registration; robust cost functions; search algorithm; stochastic search; surface interpenetration measure; Biomedical imaging; Convergence; Cost function; Genetic algorithms; Image registration; Iterative algorithms; Iterative closest point algorithm; Medical robotics; Noise robustness; Stochastic resonance; Index Terms- Range image registration; genetic algorithms; robust methods; stochastic search.; Algorithms; Artificial Intelligence; Image Enhancement; Image Interpretation, Computer-Assisted; Imaging, Three-Dimensional; Information Storage and Retrieval; Numerical Analysis, Computer-Assisted; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity; Signal Processing, Computer-Assisted; Subtraction Technique;
fLanguage :
English
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher :
ieee
ISSN :
0162-8828
Type :
jour
DOI :
10.1109/TPAMI.2005.108
Filename :
1407879
Link To Document :
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