Publications

@article{alegre_surface_2010,

title = {Surface finish control in machining processes using haralick descriptors and neuronal networks},

author = {Enrique Alegre and Rocío Alaiz-Rodríguez and Joaquín Barreiro and Eduardo Fidalgo and Laura Fernández-Robles},

url = {https://link.springer.com/chapter/10.1007/978-3-642-12712-0_21},

year  = {2010},

date = {2010-01-01},

journal = {Computational Modeling of Objects Represented in Images: Second International Symposium, CompIMAGE 2010, Buffalo, NY, USA, May 5-7, 2010. Proceedings 2},

pages = {231–241},

abstract = {This paper presents a computer vision-based method to control surface roughness in steel parts. It classifies steel surfaces into acceptable and defective classes based on roughness. The study uses 143 images of AISI 303 stainless steel and three image description methods: texture local filters, Haralick descriptors, and wavelet transform features. The best error rate of 4.0% was achieved using texture descriptors with K-NN, while the optimal configuration with a neural network achieved a 0.0% error rate using Haralick descriptors.},

note = {Publisher: Springer Berlin Heidelberg},

keywords = {Classification Methods, Computer vision, Haralick Descriptors, Surface Finish Control, surface roughness},

pubstate = {published},

tppubtype = {article}

}