PERSONAL AUTHENTICATION BASED ON HAND DORSA VEIN IMAGES
Personal authentication is a way to verify or identify a person from a given data. There are many way are use to verify a person. For example based on hand geometry, fingerprint, iris, face and hand vein. While in this project, hand dorsa vein images are used to verify the person. Every person...
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| Main Author: | |
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| Format: | Final Year Project Report / IMRAD |
| Language: | en en en |
| Published: |
Universiti Malaysia Sarawak, (UNIMAS)
2010
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| Subjects: | |
| Online Access: | http://ir.unimas.my/id/eprint/49785/1/Shah%20Hida%20%28dsva%29.pdf http://ir.unimas.my/id/eprint/49785/2/Shah%20Hida%2024%20pgs.pdf http://ir.unimas.my/id/eprint/49785/3/Shah%20Hida%20ft.pdf http://ir.unimas.my/id/eprint/49785/ |
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| Summary: | Personal authentication is a way to verify or identify a person from a given data.
There are many way are use to verify a person. For example based on hand geometry,
fingerprint, iris, face and hand vein. While in this project, hand dorsa vein images are
used to verify the person. Every person has a unique set of blood veins in his or her
hand. Veins are very complicated therefore contain lots of different lcatures that help to
identify a person. In this project there are 2 categories that is image preprocessing and
post-processing. Image preprocessing is mainly to make the images clearer while post
processing is a process to verify the images.
In image preprocessing, there are 3 steps to process it that is noise reduction,
image segmentation and image extraction to get the region of interest. As for post
processing backpropagation neural net are used as a method to train and testing the
image. Then Principle Component Analysis is use to extract the feature vector. Only one
feature vector was selected randomly for each person. Then a image of each person will
be trained one by one. The value of the weight taken from the training will he updated in
a database. 60 images for training which consists of 45 images from the same person
that have in database while 15 images are other person images. Images verification was
done by one- to- many. The performances were evaluated using False Acceptance Rate
(FAR) and False Rejection Rate (FRR) |
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