Our aim is to discuss three approaches to the detection of defects in continuous production processes, which are based on local methods of processing image sequences. These approaches are motivated by and applicable to images of hot metals or other surfaces, which are uniform at a macroscopic level, when defects are not present. The first of them is based on the estimation of fractal dimensions of image cross-sections. The second and third approaches are compositions of known techniques, which are selected and tuned to our goal. We discuss their advantages and disadvantages, since they provide different information on defects. The results of their testing on 12 industrial images are also summarized.
@article{bwmeta1.element.bwnjournal-article-amcv18i4p581bwm,
author = {Ewaryst Rafaj\l owicz and Marek Wnuk and Wojciech Rafaj\l owicz},
title = {Local detection of defects from image sequences},
journal = {International Journal of Applied Mathematics and Computer Science},
volume = {18},
year = {2008},
pages = {581-592},
zbl = {1156.93398},
language = {en},
url = {http://dml.mathdoc.fr/item/bwmeta1.element.bwnjournal-article-amcv18i4p581bwm}
}
Ewaryst Rafajłowicz; Marek Wnuk; Wojciech Rafajłowicz. Local detection of defects from image sequences. International Journal of Applied Mathematics and Computer Science, Tome 18 (2008) pp. 581-592. http://gdmltest.u-ga.fr/item/bwmeta1.element.bwnjournal-article-amcv18i4p581bwm/
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