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Using Local Features to Classify Objects having Printable Codes

Filipe Ferreira, Luis Davim, Rui Rocha, Vítor Silva, Jorge Dias

In Proc. of Int. Conf. 5th Workshop on European Scientific and Industrial Collaboration on promoting Advanced Technologies in Manufacturing (WESIC’07), Warsaw, Poland, 21-22 Jun. 2007.


Abstract

The concept of tracking the component origin and manufacturing specification encoded in the form of Data-Matrices has been gaining ground. This has translated into a search for cost-effective alternatives to machine readable, printable codes such as barcodes. The advantage of Data-Matrices assumes special relevance in the case of miniature components and in the case of complex, multi-part assemblies in which a large amount of information must be encoded within a small foot-print. We propose the application of state of the art techniques in multi-scale, local image feature extraction (Corners and lines) to read the binary data in Data-Matrices. The columns of binary data are arranged in the form of a sequence of binary features each of which codes some information. Our aim is to increase the applicability of the codes by developing applications in object classification without supervision, achieving tolerance to incomplete information about the objects to be classified. The classification process is achieved by using techniques that are commonly utilized in bio-informatics to align protein sequence which recently have been applied to Place recognition problems in Mobile Robot Navigation.


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BibTeX

@INPROCEEDINGS(Ferreira_et_al_07,

     AUTHOR = "Ferreira, F. and Davim, L. and Rocha, R. and Silva, V. and Dias, J.",

     TITLE = "Using Local Features to Classify Objects having Printable Codes",

     BOOKTITLE = "Proc. of Int. Conf. 5$^{th}$ Workshop on European Scientific and Industrial Collaboration on promoting Advanced Technologies in Manufacturing (WESIC’07)",

     ADDRESS = "Warsaw, Poland",

     YEAR = "2007",

     MONTH = "Jun."

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Last update: 13/06/2007