Industrial non-intrusive coded-target identification and decoding application

Miguel Fernandez-Fernandez; Carmen Alonso-Montes; A. Bertelsen; A. Mendikute

doi:10.1007/978-3-642-38628-2_94

Industrial non-intrusive coded-target identification and decoding application

Miguel Fernandez-Fernandez
, Carmen Alonso-Montes
, A. Bertelsen
, A. Mendikute

IDEKO

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

7 Citations (Scopus)

Abstract

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.

Original language	English
Title of host publication	Pattern Recognition and Image Analysis - 6th Iberian Conference, IbPRIA 2013, Proceedings
Pages	790-797
Number of pages	8
DOIs	https://doi.org/10.1007/978-3-642-38628-2_94
Publication status	Published - 2013
Externally published	Yes
Event	6th Iberian Conference on Pattern Recognition and Image Analysis, IbPRIA 2013 - Funchal, Madeira, Portugal Duration: 5 Jun 2013 → 7 Jun 2013

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	7887 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	6th Iberian Conference on Pattern Recognition and Image Analysis, IbPRIA 2013
Country/Territory	Portugal
City	Funchal, Madeira
Period	5/06/13 → 7/06/13

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 9 Industry, Innovation, and Infrastructure

Keywords

coded-target
industrial application
segmentation

Access to Document

10.1007/978-3-642-38628-2_94

Cite this

Fernandez-Fernandez, M., Alonso-Montes, C., Bertelsen, A., & Mendikute, A. (2013). Industrial non-intrusive coded-target identification and decoding application. In Pattern Recognition and Image Analysis - 6th Iberian Conference, IbPRIA 2013, Proceedings (pp. 790-797). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7887 LNCS). https://doi.org/10.1007/978-3-642-38628-2_94

Fernandez-Fernandez, Miguel ; Alonso-Montes, Carmen ; Bertelsen, A. et al. / Industrial non-intrusive coded-target identification and decoding application. Pattern Recognition and Image Analysis - 6th Iberian Conference, IbPRIA 2013, Proceedings. 2013. pp. 790-797 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{ed358b2b24304fcd92d04f19306f66d8,

title = "Industrial non-intrusive coded-target identification and decoding application",

abstract = "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.",

keywords = "coded-target, industrial application, segmentation",

author = "Miguel Fernandez-Fernandez and Carmen Alonso-Montes and A. Bertelsen and A. Mendikute",

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doi = "10.1007/978-3-642-38628-2\_94",

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Fernandez-Fernandez, M, Alonso-Montes, C, Bertelsen, A & Mendikute, A 2013, Industrial non-intrusive coded-target identification and decoding application. in Pattern Recognition and Image Analysis - 6th Iberian Conference, IbPRIA 2013, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 7887 LNCS, pp. 790-797, 6th Iberian Conference on Pattern Recognition and Image Analysis, IbPRIA 2013, Funchal, Madeira, Portugal, 5/06/13. https://doi.org/10.1007/978-3-642-38628-2_94

Industrial non-intrusive coded-target identification and decoding application. / Fernandez-Fernandez, Miguel; Alonso-Montes, Carmen; Bertelsen, A. et al.
Pattern Recognition and Image Analysis - 6th Iberian Conference, IbPRIA 2013, Proceedings. 2013. p. 790-797 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7887 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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 -

Fernandez-Fernandez M, Alonso-Montes C, Bertelsen A, Mendikute A. Industrial non-intrusive coded-target identification and decoding application. In Pattern Recognition and Image Analysis - 6th Iberian Conference, IbPRIA 2013, Proceedings. 2013. p. 790-797. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-642-38628-2_94

Industrial non-intrusive coded-target identification and decoding application

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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