Publications
2012
1.
Morala-Argüello, Patricia; Barreiro, Joaquín; Alegre, Enrique
A evaluation of surface roughness classes by computer vision using wavelet transform in the frequency domain Artículo de revista
En: The International Journal of Advanced Manufacturing Technology, vol. 59, pp. 213–220, 2012, (Publisher: Springer-Verlag).
Resumen | Enlaces | BibTeX | Etiquetas: neural networks, quality inspection, surface roughness, texture analysis, wavelet transform
@article{morala-arguello_evaluation_2012,
title = {A evaluation of surface roughness classes by computer vision using wavelet transform in the frequency domain},
author = {Patricia Morala-Argüello and Joaquín Barreiro and Enrique Alegre},
url = {https://link.springer.com/article/10.1007/s00170-011-3480-6},
year = {2012},
date = {2012-01-01},
journal = {The International Journal of Advanced Manufacturing Technology},
volume = {59},
pages = {213–220},
abstract = {This study proposes a multiresolution method for unmanned visual quality inspection and surface roughness discrimination in turning. Using wavelet transform, texture features were extracted from surface images, focusing on gray levels in vertical detail sub-images. A multilayer Perceptron neural network classified textures, achieving error rates between 2.59% and 4.17%.},
note = {Publisher: Springer-Verlag},
keywords = {neural networks, quality inspection, surface roughness, texture analysis, wavelet transform},
pubstate = {published},
tppubtype = {article}
}
This study proposes a multiresolution method for unmanned visual quality inspection and surface roughness discrimination in turning. Using wavelet transform, texture features were extracted from surface images, focusing on gray levels in vertical detail sub-images. A multilayer Perceptron neural network classified textures, achieving error rates between 2.59% and 4.17%.
2.
Argüello, Patricia Morala; Barreiro, Joaquín; Alegre, Enrique
A evaluation of surface roughness classes by computer vision using wavelet transform in the frequency domain Artículo de revista
En: The International Journal of Advanced Manufacturing Technology, vol. 59, pp. 213–220, 2012, (Publisher: Springer-Verlag).
Resumen | Enlaces | BibTeX | Etiquetas: neural networks, quality inspection, surface roughness, texture analysis, wavelet transform
@article{morala_arguello_evaluation_2012,
title = {A evaluation of surface roughness classes by computer vision using wavelet transform in the frequency domain},
author = {Patricia Morala Argüello and Joaquín Barreiro and Enrique Alegre},
url = {https://link.springer.com/article/10.1007/s00170-011-3480-6},
year = {2012},
date = {2012-01-01},
journal = {The International Journal of Advanced Manufacturing Technology},
volume = {59},
pages = {213–220},
abstract = {This study proposes a multiresolution method for unmanned visual quality inspection and surface roughness discrimination in turning. Using wavelet transform, texture features were extracted from surface images, focusing on gray levels in vertical detail sub-images. A multilayer Perceptron neural network classified textures, achieving error rates between 2.59% and 4.17%.},
note = {Publisher: Springer-Verlag},
keywords = {neural networks, quality inspection, surface roughness, texture analysis, wavelet transform},
pubstate = {published},
tppubtype = {article}
}
This study proposes a multiresolution method for unmanned visual quality inspection and surface roughness discrimination in turning. Using wavelet transform, texture features were extracted from surface images, focusing on gray levels in vertical detail sub-images. A multilayer Perceptron neural network classified textures, achieving error rates between 2.59% and 4.17%.
2009
3.
Morala-Argueello, Patricia; Alegre, Enrique; Suarez, Sir; Gonzalez-Castro, Victor; Barreiro, Joaquín
QUALITIVE SURFACE ROUGHNESS EVALUATION USING HARALICK FEATURES AND WAVELET TRANSFORM. Artículo de revista
En: Annals of DAAAM & Proceedings, 2009.
Resumen | Enlaces | BibTeX | Etiquetas: Automated Vision System, Haralick Features, Surface Finish Classification, wavelet transform
@article{morala-argueello_qualitive_2009,
title = {QUALITIVE SURFACE ROUGHNESS EVALUATION USING HARALICK FEATURES AND WAVELET TRANSFORM.},
author = {Patricia Morala-Argueello and Enrique Alegre and Sir Suarez and Victor Gonzalez-Castro and Joaquín Barreiro},
url = {https://openurl.ebsco.com/EPDB%3Agcd%3A10%3A28782154/detailv2?sid=ebsco%3Aplink%3Ascholar-a&id=ebsco%3Agcd%3A47081114&crl=c&jrnl=17269679&id_token_hint=eyJraWQiOiIxNjg2MTQ5MjEzNjMxIiwiYWxnIjoiUlMyNTYifQ.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.eZENRNegI61Xbe4u0bWWNLkdMQUU0LhmDpaOpB78k-UCEP_6MoiccAupzgRxrOu8pX28n6styjtAMyQinyrisZEOxtq0ME2Jnv_oJ6x7pGuUWSrwvI-WgQqqWiZ5flbL4jopLZsgmwDHbFDJe6OIa8Gn-HvwgTOYJRHFCzsJj6qegsuQzukkPRRlat_JXK0eMAzD93rITuwfB9SepfezSD1TWKz63m0ynv56MyQYkKXaEWZnmUQESOT6Qk2Mb4IgxuPO9r-6j5ImCDfsqojX99lPE6fT1WpwAGFLh7m2cKXKtVfSP6k6i6vM25Bn7Z8-s3fDxpRtvUCbxX-L4B1fVw&link_origin=scholar.google.es},
year = {2009},
date = {2009-01-01},
journal = {Annals of DAAAM & Proceedings},
abstract = {This paper discusses the development of an automated vision system for classifying surface finish in turning parts using Haralick features in the frequency domain through wavelet transform. The study compares images of parts with low and high roughness, extracting Haralick features for image description. Classification is carried out using the k-nearest neighbors (KNN) algorithm, and the results are compared with other simpler features based on moments.},
keywords = {Automated Vision System, Haralick Features, Surface Finish Classification, wavelet transform},
pubstate = {published},
tppubtype = {article}
}
This paper discusses the development of an automated vision system for classifying surface finish in turning parts using Haralick features in the frequency domain through wavelet transform. The study compares images of parts with low and high roughness, extracting Haralick features for image description. Classification is carried out using the k-nearest neighbors (KNN) algorithm, and the results are compared with other simpler features based on moments.