Publications

@article{alegre_computer_2008,

title = {Computer vision and classification techniques on the surface finish control in machining processes},

author = {Enrique Alegre and Joaquín Barreiro and Manuel Castejón-Limas and S Suárez},

url = {https://link.springer.com/chapter/10.1007/978-3-540-69812-8_110},

year  = {2008},

date = {2008-01-01},

urldate = {2008-01-01},

journal = {International Conference Image Analysis and Recognition},

pages = {1101–1110},

abstract = {This work presents a method for surface finish control using computer vision. The test parts were made of AISI 303 stainless steel and machined with a CNC lathe. Using a Pulnix camera, diffuse illumination, and industrial zoom, 140 images were captured. Three feature extraction methods were applied: histogram statistics, Haralick descriptors, and Laws descriptors. Using k-NN, the best hit rate achieved was 92.14% with unfiltered images using Laws features. These results demonstrate the feasibility of using texture descriptors to assess the roughness of metallic parts for quality inspection.},

note = {Publisher: Springer Berlin Heidelberg Berlin, Heidelberg},

keywords = {AISI 303, Computer vision, Product Quality Inspection, Surface Finish Control, texture descriptors},

pubstate = {published},

tppubtype = {article}

}