Definition of Foot Size Model using Kohonen Network
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 32797
Definition of Foot Size Model using Kohonen Network

Authors: Khawla Ben Abderrahim

Abstract:

In order to define a new model of Tunisian foot sizes and for building the most comfortable shoes, Tunisian industrialists must be able to offer for their customers products able to put on and adjust the majority of the target population concerned. Moreover, the use of models of shoes, mainly from others country, causes a mismatch between the foot and comfort of the Tunisian shoes. But every foot is unique; these models become uncomfortable for the Tunisian foot. We have a set of measures produced from a 3D scan of the feet of a diverse population (women, men ...) and we try to analyze this data to define a model of foot specific to the Tunisian footwear design. In this paper we propose tow new approaches to modeling a new foot sizes model. We used, indeed, the neural networks, and specially the Kohonen network. Next, we combine neural networks with the concept of half-foot size to improve the models already found. Finally, it was necessary to compare the results obtained by applying each approach and we decide what-s the best approach that give us the most model of foot improving more comfortable shoes.

Keywords: Morphology of the foot, foot size, half foot size, neural network, Kohonen network, model of foot size.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1056663

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1509

References:


[1] BOUTEILLER J.M., MARCHESSOUX C, FERNANDEZ, « Comparison study between 3d modelling of human foot", 3D Human Modelling, Paris, avril 2003.
[2] MARCHESSOUX Cédric, "Système d-acquisition 3D pour le pied humain", 12 décembre 2003.
[3] THEVENET J.M. "Rêves de pompes, pompes de rêves", Janvier 1988.
[4] Teuvo Kohonen, "Self-organized formation of topologically correct feature maps. Biol". Cybernetics, volume 43.
[5] Teuvo Kohonen, "Self-Organizing Maps", Springer, Berlin, Germany
[6] Naima SANAA, Sarra TRABELSI, Nourreddine HAMDOUN, Mahmoud MANSOURI, Mohamed Elakremi BRAHMI, Amara ZADDEM, "Caractérisation de la morphologie du pied Tunisien et développement d'une technique adaptée pour la chaussure tunisienne", Juin 2008
[7] Olfa KANOUN, Mohamed Hedi KALLEL & Mohamed Salim BOUHLEL « Adaptativité du Quantificateur Vectoriel ├á la Compression d-Images Médicales par Réseau de Neurones » U. R. Sciences Et Technologie de l-Image et des Télécommunications (SETIT) , 2007.
[8] Kristof Van Laerhoven "Introducrtion to an artificial neural network", 2007.
[9] P.DEGOULET, M.FIESCHI, "Informatique médicale ",3éme édition, Masson », 1998.