Sift technique on extraction of fingerprint features

This project has a final goal of implementing the Scale-invariant feature transform (or SIFT) algorithm towards fingerprint features extraction. The algorithms comprise of scale space construction, keypoint localization, orientation assignment and keypoint descriptor. The scale space construction is...

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Main Author:	Lee, Han Huei
Format:	Thesis
Published:	2010
Subjects:	TK Electrical engineering Electronics Nuclear engineering
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id	my-utm-ep.26972
record_format	uketd_dc
spelling	my-utm-ep.269722017-08-14T03:21:39Z Sift technique on extraction of fingerprint features 2010 Lee, Han Huei TK Electrical engineering. Electronics Nuclear engineering This project has a final goal of implementing the Scale-invariant feature transform (or SIFT) algorithm towards fingerprint features extraction. The algorithms comprise of scale space construction, keypoint localization, orientation assignment and keypoint descriptor. The scale space construction is using the DOG to detect stable key points and performing neighborhood comparison to detect the scale space extrema. Next the keypoint localization algorithm will be using the Taylor Expansion theory to reject the unstable keypoint which is low contrast. Subsequently, the orientation also will be assigned to each keypoint location based on local image gradient directions. Lastly, the keypoint descriptor is used to compute descriptor vectors which is highly distinctive. After implementing the SIFT algorithms, it is used to validate against all sort of common invariance and the outcome results are showing good accuracy. Conclusion, SIFT finds accurate features against those common invariances, such as scale invariance, rotation and illumination. 2010 Thesis http://eprints.utm.my/id/eprint/26972/ masters Universiti Teknologi Malaysia, Faculty of Electrical Engineering Faculty of Electrical Engineering
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
topic	TK Electrical engineering Electronics Nuclear engineering
spellingShingle	TK Electrical engineering Electronics Nuclear engineering Lee, Han Huei Sift technique on extraction of fingerprint features
description	This project has a final goal of implementing the Scale-invariant feature transform (or SIFT) algorithm towards fingerprint features extraction. The algorithms comprise of scale space construction, keypoint localization, orientation assignment and keypoint descriptor. The scale space construction is using the DOG to detect stable key points and performing neighborhood comparison to detect the scale space extrema. Next the keypoint localization algorithm will be using the Taylor Expansion theory to reject the unstable keypoint which is low contrast. Subsequently, the orientation also will be assigned to each keypoint location based on local image gradient directions. Lastly, the keypoint descriptor is used to compute descriptor vectors which is highly distinctive. After implementing the SIFT algorithms, it is used to validate against all sort of common invariance and the outcome results are showing good accuracy. Conclusion, SIFT finds accurate features against those common invariances, such as scale invariance, rotation and illumination.
format	Thesis
qualification_level	Master's degree
author	Lee, Han Huei
author_facet	Lee, Han Huei
author_sort	Lee, Han Huei
title	Sift technique on extraction of fingerprint features
title_short	Sift technique on extraction of fingerprint features
title_full	Sift technique on extraction of fingerprint features
title_fullStr	Sift technique on extraction of fingerprint features
title_full_unstemmed	Sift technique on extraction of fingerprint features
title_sort	sift technique on extraction of fingerprint features
granting_institution	Universiti Teknologi Malaysia, Faculty of Electrical Engineering
granting_department	Faculty of Electrical Engineering
publishDate	2010
_version_	1747815556127391744

Sift technique on extraction of fingerprint features

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