Design of a pattern recognition system in thermographic and footprint images for flatfoot identification in children between five and six years old
| dc.contributor.author | Muñoz-Neira , Milton Javier | spa |
| dc.contributor.author | Martínez-Parra, Anyed Stephany | spa |
| dc.contributor.author | Ruiz-Adarme, Cristian Gerardo | spa |
| dc.contributor.author | Triana-Castro, Carlos Humberto | spa |
| dc.contributor.author | Cornejo-Plata, Jorge Luis | spa |
| dc.date | 2019-08-13 | |
| dc.date.accessioned | 2019-09-19T21:09:37Z | |
| dc.date.available | 2019-09-19T21:09:37Z | |
| dc.description | The following paper presents the main results of an exploratory research oriented to design and implementation of a pattern recognition system for flatfoot identification in children between 5 and 6 years. Patterns were determined from texture analysis of foot thermographic images, and from contour analysis of footprint images. For each case, an artificial neuronal network was trained, with base in a back propagation algorithm. In each trial, 70% of data were used for training, and 30% for validation. For experiments done, success rates greater than 80% were achieved. The best results was reached with contour patterns reduced by PCA, in a binary system, with a success rate of 90.84% in cross validation. Results are a contribution to study of diagnostic techniques for flatfoot treatment through use of technologic tools. | en-US |
| dc.description | The following paper presents the main results of exploratory research-oriented to the design and implementation of a pattern recognition system for flatfoot identification in children between 5 and 6 years. Patterns were determined from texture analysis of foot thermographic images, and from contour analysis of footprint images. For each case, an artificial neuronal network was trained, with base in a back-propagation algorithm. In each trial, 70 % of data were used for training, and 30 % for validation. For experiments done, success rates greater than 80 % were achieved. The best results were reached with contour patterns reduced by principal components analysis, PCA, in a binary system, with a success rate of 90.84 % in cross-validation. Results are a contribution to the study of diagnostic techniques for flatfoot treatment through the use of technologic tools. | es-ES |
| dc.format | application/pdf | |
| dc.identifier | https://revistas.udistrital.edu.co/index.php/revcie/article/view/14345 | |
| dc.identifier.uri | http://hdl.handle.net/11349/16965 | |
| dc.language | spa | |
| dc.publisher | Universidad Distrital Francisco José de Caldas | es-ES |
| dc.relation | https://revistas.udistrital.edu.co/index.php/revcie/article/view/14345/15149 | |
| dc.rights | Derechos de autor 2019 MILTON JAVIER MUÑOZ NEIRA, Anyed Stephany Martínez Parra, Cristian Gerardo Ruiz Adarme, Carlos Humberto Triana Castro, Jorge Luis Cornejo Plata | es-ES |
| dc.rights | https://creativecommons.org/licenses/by-nc-sa/4.0 | es-ES |
| dc.source | Revista Científica; Vol 3 No 36 (2019): sep-dic | en-US |
| dc.source | Revista científica; Vol. 3 Núm. 36 (2019): sep-dic | es-ES |
| dc.source | 2344-8350 | |
| dc.source | 0124-2253 | |
| dc.subject | flatfoot | en-US |
| dc.subject | texture patterns | en-US |
| dc.subject | footprint patterns | en-US |
| dc.subject | artificial neuronal networks | en-US |
| dc.subject | pie plano | es-ES |
| dc.subject | patrones de textura | es-ES |
| dc.subject | patrones de huella | es-ES |
| dc.subject | redes neuronales artificiales | es-ES |
| dc.title | Design of a pattern recognition system in thermographic and footprint images for flatfoot identification in children between five and six years old | en-US |
| dc.title | Diseño de un sistema de reconocimiento de patrones en imágenes termográficas y de huella plantar para la identificación de pie plano en niños con edades entre cinco y seis años | es-ES |
| dc.type | info:eu-repo/semantics/article | |
| dc.type | info:eu-repo/semantics/publishedVersion | |
| dc.type.coar | http://purl.org/coar/resource_type/c_6501 |