Please use this identifier to cite or link to this item:
https://hdl.handle.net/10356/3601
Title: | Fingerprint feature extraction | Authors: | Tin Tin Aye. | Keywords: | DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Biometrics | Issue Date: | 2003 | Abstract: | This dissertation focuses on extraction of minutiae from the gray fingerprint images directly without going through the usual binarization and thinning processes. Multilayer feedforward neural network is used for extraction of minutiae. Two types of most commonly used minutiae, bifurcations and ridge endings, are extracted. If the feature is not bifurcation or ridge ending, we name this image as the 'none' image class. | URI: | http://hdl.handle.net/10356/3601 | Schools: | School of Electrical and Electronic Engineering | Rights: | Nanyang Technological University | Fulltext Permission: | restricted | Fulltext Availability: | With Fulltext |
Appears in Collections: | EEE Theses |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
EEE-THESES_1447.pdf Restricted Access | 15.8 MB | Adobe PDF | View/Open |
Page view(s) 50
420
Updated on Mar 28, 2024
Download(s)
2
Updated on Mar 28, 2024
Google ScholarTM
Check
Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.