Resumen
It is proposed to develop a prototype platform based on artificial vision that allows us to identify the defects that ceramic tiles have, with which we can classify them according to their quality. The algorithms chosen to develop the platform are Support Vector Machine (SVM) and K-Nearest Neighbor (KNN). The SVM algorithm has the characteristic that, a priori, we know the classes to which our individuals belong, it is not a grouping by similarities, but we have well-defined classes, in the treatment of images there is a high percentage of effectiveness of this algorithm. On the other hand, because of its ease of implementation, the KNN algorithm is one of the most widely used non-parametric classifiers. Its theoretical properties guarantee that its error probability is bounded by twice the Bayesian error probability, in the treatment of images with this algorithm there are high percentages of effectiveness in the classification The necessary parameters are established for the proposal based on the study of related works and the same application methodology is presented, which contemplates the pre-processing of the images, the obtaining of the descriptors, the use of the algorithms and the results obtained.
Idioma original | Inglés |
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Título de la publicación alojada | Advances in Artificial Intelligence, Software and Systems Engineering - Proceedings of the AHFE 2021 Virtual Conferences on Human Factors in Software and Systems Engineering, Artificial Intelligence and Social Computing, and Energy, 2021 |
Editores | Tareq Z. Ahram, Waldemar Karwowski, Jay Kalra |
Editorial | Springer Science and Business Media Deutschland GmbH |
Páginas | 223-229 |
Número de páginas | 7 |
ISBN (versión impresa) | 9783030806231 |
DOI | |
Estado | Publicada - 2021 |
Evento | AHFE Conferences on Human Factors in Software and Systems Engineering, Artificial Intelligence and Social Computing, and Energy, 2021 - Virtual, Online Duración: 25 jul. 2021 → 29 jul. 2021 |
Serie de la publicación
Nombre | Lecture Notes in Networks and Systems |
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Volumen | 271 |
ISSN (versión impresa) | 2367-3370 |
ISSN (versión digital) | 2367-3389 |
Conferencia
Conferencia | AHFE Conferences on Human Factors in Software and Systems Engineering, Artificial Intelligence and Social Computing, and Energy, 2021 |
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Ciudad | Virtual, Online |
Período | 25/07/21 → 29/07/21 |
Nota bibliográfica
Publisher Copyright:© 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.