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Development of evolution based technology for Image Recognition Systems

Sandvik, Jens-Petter Skjelvåg
Master thesis
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Hovedoppgave_Jens-Petter_Sandvik.pdf (1.426Mb)
Year
2005
Permanent link
http://urn.nb.no/URN:NBN:no-11481

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  • Institutt for informatikk [3608]
Abstract
A traffic sign detection system in the vehicle can be of great help

for the driver. The number of accidents can be reduced by 20\% if the

speed limits are followed. A system that warns the driver about speeding could therefore save lives if the driver reduces the speed.

This work focus on the colour classification used in traffic sign

detection methods. Existing methods are compared, and a Genetic

Algorithm is used for optimising parameters used in the existing

colour classification methods.

Cartesian Genetic Programming is used for evolving colour classifiers

for traffic signs, and compared to the existing methods. The evolved

classifier is tested with three different luminance adjustment

algorithms.

The results show that the GA is able to find better parameters than

the reported parameters, and some of the evolved colour classifiers were

better than the existing methods. The CGP architecture did find better

classifiers than the existing. The luminance adjustment algorithms did

not result in better classification results.
 
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