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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier8JMKD3MGPBW34M/3A3LH85
Repositorysid.inpe.br/sibgrapi/2011/07.11.00.23
Last Update2011:07.11.01.01.55 (UTC) administrator
Metadata Repositorysid.inpe.br/sibgrapi/2011/07.11.00.23.35
Metadata Last Update2022:06.14.00.07.16 (UTC) administrator
DOI10.1109/SIBGRAPI.2011.16
Citation KeyBelussiHira:2011:FaQRCo
TitleFast QR code detection in arbitrarily acquired images
FormatDVD, On-line.
Year2011
Access Date2024, Apr. 29
Number of Files1
Size2946 KiB
2. Context
Author1 Belussi, Luiz Felipe Franco
2 Hirata, Nina Sumiko Tomita
Affiliation1 Institute of Mathematics and Statistics, University of São Paulo
2 Institute of Mathematics and Statistics, University of São Paulo
EditorLewiner, Thomas
Torres, Ricardo
e-Mail Addressnina@ime.usp.br
Conference NameConference on Graphics, Patterns and Images, 24 (SIBGRAPI)
Conference LocationMaceió, AL, Brazil
Date28-31 Aug. 2011
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Book TitleProceedings
Tertiary TypeFull Paper
History (UTC)2011-07-23 15:36:12 :: nina@ime.usp.br -> administrator :: 2011
2022-06-14 00:07:16 :: administrator -> :: 2011
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Version Typefinaldraft
KeywordsQR code
2D barcode
Haar-like features
cascade classifier
boosting
classification
pattern recognition
AbstractThe detection of QR codes, a type of 2D barcode, as described in the literature consists merely in the determination of the boundaries of the symbol region in images obtained with the specific intent of highlighting the symbol. However, many important applications such as those related with accessibility technologies or robotics, depends on first detecting the presence of a barcode in an environment. We employ Viola-Jones rapid object detection framework to address the problem of finding QR codes in arbitrarily acquired images. This framework provides an efficient way to focus the detection process in promising regions of the image and a very fast feature calculation approach for pattern classification. An extensive study of variations in the parameters of the framework for detecting finder patterns, present in three corners of every QR code, was carried out. Detection accuracy superior to 90%, with controlled number of false positives, is achieved. We also propose a post-processing algorithm that aggregates the results of the first step and decides if the detected finder patterns are part of QR code symbols. This two-step processing is done in real time.
Arrangement 1urlib.net > SDLA > Fonds > SIBGRAPI 2011 > Fast QR code...
Arrangement 2urlib.net > SDLA > Fonds > Full Index > Fast QR code...
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4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPBW34M/3A3LH85
zipped data URLhttp://urlib.net/zip/8JMKD3MGPBW34M/3A3LH85
Languageen
Target File86622_final.pdf
User Groupnina@ime.usp.br
Visibilityshown
5. Allied materials
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPEW34M/46SKNPE
8JMKD3MGPEW34M/4742MCS
Citing Item Listsid.inpe.br/sibgrapi/2022/05.15.00.56 3
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
6. Notes
Empty Fieldsarchivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination documentstage edition electronicmailaddress group isbn issn label lineage mark nextedition notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project readergroup readpermission resumeid rightsholder schedulinginformation secondarydate secondarykey secondarymark secondarytype serieseditor session shorttitle sponsor subject tertiarymark type url volume


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