Full metadata record
DC FieldValueLanguage
dc.contributor.authorSun, Shu-Kuoen_US
dc.contributor.authorChen, Zenen_US
dc.date.accessioned2014-12-08T15:11:58Z-
dc.date.available2014-12-08T15:11:58Z-
dc.date.issued2011-03-01en_US
dc.identifier.issn1016-2364en_US
dc.identifier.urihttp://hdl.handle.net/11536/9186-
dc.description.abstractIn the paper, a new recognition method for logos imaged by mobile phone cameras is presented which can be incorporated with mobile phone services for use in enterprise identification, corporate website access, traffic sign reading, security check, content awareness, and the related applications. The main challenge in applying the logo recognition for mobile phone applications is the inevitable photometric and geometric transformations encountered when a handheld mobile phone camera operates at a varying viewpoint under different lighting environments. A new distinctive logo feature vector and an associated similarity measure are proposed for logo recognition using the Zernike moment (ZM) phase information. The discriminative power of the new logo recognition method is compared with three major existing methods. The experimental results indicate that the proposed ZM phase method has the best performance in terms of the precision and recall criterion under the above inevitable imaging variations. An analysis on the performances of the four recognition methods is given to account for the performance discrepancy.en_US
dc.language.isoen_USen_US
dc.subjectlogo recognition and retrievalen_US
dc.subjectmobile phone cameraen_US
dc.subjectgeometric and photometric transformationsen_US
dc.subjectZernike momentsen_US
dc.subjectphase and magnitude informationen_US
dc.subjectprecision and recallen_US
dc.titleRobust Logo Recognition for Mobile Phone Applicationsen_US
dc.typeArticleen_US
dc.identifier.journalJOURNAL OF INFORMATION SCIENCE AND ENGINEERINGen_US
dc.citation.volume27en_US
dc.citation.issue2en_US
dc.citation.spage545en_US
dc.citation.epage559en_US
dc.contributor.department資訊工程學系zh_TW
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.identifier.wosnumberWOS:000289122300010-
dc.citation.woscount2-
Appears in Collections:Articles


Files in This Item:

  1. 000289122300010.pdf

If it is a zip file, please download the file and unzip it, then open index.html in a browser to view the full text content.