Fingerprint classification based on genetic programming

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InProceedings{Hu:2010:ICCET,

• author = "Jiaojiao Hu and Mei Xie",
• title = "Fingerprint classification based on genetic programming",
• booktitle = "2nd International Conference on Computer Engineering and Technology (ICCET), 2010",
• year = "2010",
• month = "16-18 " # apr,
• volume = "6",
• pages = "V6--193--V6--196",
• abstract = "In this paper, we present a novel algorithm for fingerprint classification. This algorithm classifies a fingerprint image into one of the five classes: Arch, Left loop, Right loop, Whorl, and Tented arch. Initially, preprocessing of fingerprint images is carried out to enhance the image. Then we use genetic programming (GP) to generate new features from the original dataset without prior knowledge. Finally we can classify the fingerprint through a combination of BP network and SVM classifiers, which can not only supplement their advantages, but also improve the computation efficiency. We experiment this algorithm on database from FVC2004. For the five-class problem, a classification accuracy of 93.6percent without any reject, and classification accuracy of 96.2percent with a 15percent reject rate. For the four-class problem (arch and tented arch combined into one class), classification error can be reduced to 3.6percent with only 7.2percent reject rate.",
• keywords = "genetic algorithms, genetic programming, BP network, FVC2004, SVM classifier, fingerprint classification, four-class problem, image classification, backpropagation, fingerprint identification, image classification, neural nets, support vector machines",
• DOI = "doi:10.1109/ICCET.2010.5486315",
• notes = "School of Electronic Engineering, University of Electronic Science and Technology of China Chengdu, China. Also known as \cite{5486315}",

}

Genetic Programming entries for Jiaojiao Hu Mei Xie

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