Development of evolution based technology for Image Recognition Systems

Created by W.Langdon from gp-bibliography.bib Revision:1.7662

@MastersThesis{Hovedoppgave_Jens-Petter_Sandvik,

• title = "Development of evolution based technology for Image Recognition Systems",
• author = "Jens-Petter Skjelvag Sandvik",
• school = "The University Of Oslo",
• year = "2005",
• month = "4 " # nov,
• 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 percent 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.",
• bibsource = "OAI-PMH server at wo.uio.no",
• language = "eng",
• oai = "oai:digbib.uio.no/32422",
• subject = "VDP:420",
• URL = "http://urn.nb.no/URN:NBN:no-11481",
• keywords = "genetic algorithms, genetic programming, cartesian genetic programming",
• size = "115 pages",

}

Genetic Programming entries for Jens-Petter Skjelvag Sandvik

Citations