TY - GEN
T1 - Industrial non-intrusive coded-target identification and decoding application
AU - Fernandez-Fernandez, Miguel
AU - Alonso-Montes, Carmen
AU - Bertelsen, A.
AU - Mendikute, A.
PY - 2013
Y1 - 2013
N2 - Non-intrusive and automatic raw part alignment for machining process is a current challenge for industry, due to the high cost of bad machining. The use of artificial markers, such as coded-targets (CT) provides a promising technique to be applied within industrial environments due to its robustness, non-intrusive nature and low cost. In this paper, an CT identification and decoding algorithm is presented. CT are used for the geometry characterization of the raw part. Its promising results allow us to introduce their usage within a real industrial machine.
AB - Non-intrusive and automatic raw part alignment for machining process is a current challenge for industry, due to the high cost of bad machining. The use of artificial markers, such as coded-targets (CT) provides a promising technique to be applied within industrial environments due to its robustness, non-intrusive nature and low cost. In this paper, an CT identification and decoding algorithm is presented. CT are used for the geometry characterization of the raw part. Its promising results allow us to introduce their usage within a real industrial machine.
KW - coded-target
KW - industrial application
KW - segmentation
UR - https://www.scopus.com/pages/publications/84883202050
U2 - 10.1007/978-3-642-38628-2_94
DO - 10.1007/978-3-642-38628-2_94
M3 - Conference contribution
AN - SCOPUS:84883202050
SN - 9783642386275
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 790
EP - 797
BT - Pattern Recognition and Image Analysis - 6th Iberian Conference, IbPRIA 2013, Proceedings
T2 - 6th Iberian Conference on Pattern Recognition and Image Analysis, IbPRIA 2013
Y2 - 5 June 2013 through 7 June 2013
ER -
