DocumentCode :
2243619
Title :
IR image segmentation using GA-MRF with Neighborhood Labels Coding
Author :
Xiaodong, Lu ; Yuanjun, He
Author_Institution :
Coll. of Astronaut., Northwestern Polytech. Univ., Xi´´an, China
Volume :
2
fYear :
2010
fDate :
6-7 March 2010
Firstpage :
37
Lastpage :
40
Abstract :
Comparing with Simulated Annealing (SA) that is often used in the image segmentations based on Markov Random Field (MRF) models, Genetic Algorithm (GA) has been applied into reducing the computation complexity of optimization. However many scholars used GA as an optimal tool that based on the gray-scale values of pixels as individuals and limited the mutations and crossovers with the gray-level coding, which caused these algorithms sensitive to noise especially to the multiplicative noise. To avoid trapping into the low-grade imitations of canonical GA with gray-level values of pixels, the labels coding of individuals in a neighborhood instead of the gray-scale values coding is proposed in this paper. And the mutations and crossovers with labels coding in a neighborhood increased the efficiency of searching optimal and preserved the original information of images. The followed experiments with Infrared (IR) image segmentations proved that the proposal algorithm approached an acceptable result among the noise restraint, edges preservation and computation complexity.
Keywords :
Markov processes; computational complexity; edge detection; genetic algorithms; image coding; image segmentation; simulated annealing; IR image segmentation; Markov random field; computation complexity; edges preservation; genetic algorithm; gray-level coding; gray-level values; gray-scale values; infrared image segmentations; multiplicative noise; neighborhood labels coding; noise restraint; simulated annealing; Computational modeling; Genetic algorithms; Genetic mutations; Gray-scale; Image coding; Image segmentation; Infrared imaging; Markov random fields; Proposals; Simulated annealing; genetic algorithm; image segmentation; infrared image; markov random field; neighborhood label coding;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Informatics in Control, Automation and Robotics (CAR), 2010 2nd International Asia Conference on
Conference_Location :
Wuhan
ISSN :
1948-3414
Print_ISBN :
978-1-4244-5192-0
Electronic_ISBN :
1948-3414
Type :
conf
DOI :
10.1109/CAR.2010.5456522
Filename :
5456522
Link To Document :
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