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dc.contributor.authorWan Syahirah, Wan Samsudin
dc.contributor.authorSundaraj, Kenneth, Assoc. Prof. Dr.
dc.date.accessioned2012-07-19T14:55:48Z
dc.date.available2012-07-19T14:55:48Z
dc.date.issued2012-02-27
dc.identifier.urihttp://dspace.unimap.edu.my/123456789/20505
dc.descriptionInternational Conference on Man Machine Systems (ICoMMS 2012) organized by School of Mechatronic Engineering, co-organized by The Institute of Engineer, Malaysia (IEM) and Society of Engineering Education Malaysia, 27th - 28th February 2012 at Bayview Beach Resort, Penang, Malaysia.en_US
dc.description.abstractBiometric system is a system for the automated recognition of individuals based on their behavioral or biological characteristics. Biometrics are evolving drastically especially nowadays whereby there are many types of biometrics, which includes fingerprint or face pattern, and/or some aspect of behavior, such as the spoken voice, handwriting, or keystroke patterns. From all those biometric system stated the face biometric system is the most users friendly and most nonintrusive. In face biometrics, there are two types, which are in two dimensional and three dimensional recognitions. The 2D typed biometrics system is widely used, but for 3D typed biometrics is not very common but it offers more benefits than 2D. The limitation of 3D research is resulting from only few databases can be found for 3D biometrics system. The classification techniques and their success rate also been discussed in both 2D and 3D face recognition. More future work will be developed to improve the face recognition system especially in 3D recognition. This paper has discussed more on 3D face recognition which promises better future in biometrics.en_US
dc.language.isoenen_US
dc.publisherUniversiti Malaysia Perlis (UniMAP)en_US
dc.relation.ispartofseriesProceedings of the International Conference on Man-Machine Systems (ICoMMS 2012)en_US
dc.subjectFace biometricsen_US
dc.subjectFace recognitonen_US
dc.subjectRecognition rateen_US
dc.titleRecent survey on face biometric classification success ratesen_US
dc.typeWorking Paperen_US
dc.publisher.departmentSchool of Mechatronic Engineeringen_US
dc.contributor.urlwansyahirahwsamsudin@yahoo.comen_US


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