Please use this identifier to cite or link to this item:
http://dspace.unimap.edu.my:80/xmlui/handle/123456789/41775
Full metadata record
DC Field | Value | Language |
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dc.contributor.author | Hayati Hasibuan, Zainal | - |
dc.date.accessioned | 2016-05-31T06:30:32Z | - |
dc.date.available | 2016-05-31T06:30:32Z | - |
dc.date.issued | 2015-06 | - |
dc.identifier.uri | http://dspace.unimap.edu.my:80/xmlui/handle/123456789/41775 | - |
dc.description | Access is limited to UniMAP community. | en_US |
dc.description.abstract | Multimodal Biometrics is a system that are capable of using more than one physiological characteristic for verification or identification. It also refer to the automatic identification or verification of an individual. Biometric is a unique. For biometric identification, it process of trying to find out a person’s identify by comparing the present against a biometric pattern database . Here are many behaviour function in addition to physiological in which employed in biometric program for example fingerprint, iris, deal with, hearing, personal, voiceprint in addition to hands print out. Man or women identification can be separated in proof in addition to identification is dependent upon your circumstance from the request. Within multimodal biometric methods include many different distinct modalities. Multi-sensor, Multi-method, Multicharacteristic, Multi-capture/instance in addition to Multi-verifier is actually among multimodal biometric program. Biometric involve some help. By way of example, can certainly retain excessive tolerance identification placing. Also, your probability connected with accepting the impostor is actually drastically lowered. Biometric could also lower failure to sign-up rate in addition to hard to utilize phony biometric. This kind of task brings together deal with in addition to arms to become more final results. Incorporate two techniques, particularly the procedure connected with coaching in addition to assessment method. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Universiti Malaysia Perlis (UniMAP) | en_US |
dc.subject | Multimodal Biometrics | en_US |
dc.subject | Biometrics | en_US |
dc.subject | Physiological verification | en_US |
dc.subject | Palmprint | en_US |
dc.title | Information of face & palmpront multimodal biometric | en_US |
dc.type | Learning Object | en_US |
dc.contributor.advisor | Dr. Muhammad Imran Bin Ahmad | en_US |
dc.publisher.department | School of Computer and Communication Engineering | en_US |
Appears in Collections: | School of Computer and Communication Engineering (FYP) |
Files in This Item:
File | Description | Size | Format | |
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Abstract,Acknowledgement.pdf | 430.47 kB | Adobe PDF | View/Open | |
Introduction.pdf | 230.03 kB | Adobe PDF | View/Open | |
Literature Review.pdf | 813.86 kB | Adobe PDF | View/Open | |
Methodology.pdf | 463.44 kB | Adobe PDF | View/Open | |
Results and Discussion.pdf | 511.8 kB | Adobe PDF | View/Open | |
Conclusion and Recommendation.pdf | 99.92 kB | Adobe PDF | View/Open | |
Refference and Appendics.pdf | 327.17 kB | Adobe PDF | View/Open |
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