Image enhancement and segmentation on simultaneous latent fingerprint detection

A simultaneous latent fingerprint (SLF) image consists of multi-print of individual fingerprints that is lifted from a surface, typically at the crime scenes. Due to the nature and the poor quality of latent fingerprint image, segmentation becomes an important and very challenging task. This thesis...

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Main Author:	Rozita, Mohd Yusof
Format:	Thesis
Language:	English
Published:	2015
Subjects:	QA75 Electronic computers Computer science T Technology (General)
Online Access:	http://umpir.ump.edu.my/id/eprint/16374/19/Image%20enhancement%20and%20segmentation%20on%20simultaneous%20latent%20fingerprint%20detection.pdf
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spelling	my-ump-ir.163742021-12-07T04:41:46Z Image enhancement and segmentation on simultaneous latent fingerprint detection 2015-04 Rozita, Mohd Yusof QA75 Electronic computers. Computer science T Technology (General) A simultaneous latent fingerprint (SLF) image consists of multi-print of individual fingerprints that is lifted from a surface, typically at the crime scenes. Due to the nature and the poor quality of latent fingerprint image, segmentation becomes an important and very challenging task. This thesis presents an algorithm to segment individual fingerprints for SLF image. The algorithm aim to separate the fingerprint region of interest from image background, which identifies the distal phalanx portion of each finger that appears in SLF image. The algorithm utilizes ridge orientation and frequency features based on block-wise pixels. A combination of Gabor Filter and Fourier transform is implemented in the normalization stage. In the pre-processing stage, a modified version of Histogram equalization is proposed known as Alteration Histogram Equalization (AltHE). Sliding windows are applied to create bounding boxes in order to find out the distal phalanges region at the segmentation stage. To verify the capability of the proposed segmentation algorithm, the segmentation results is evaluated in two aspects: a comparison with the ground truth foreground and matching performance based on segmented region. The ground truth foreground refers to the manual mark up region of interest area. In order to evaluate the performance of this method, experiments are performed on the Indian Institute of Information Technology Database- Simultaneous Latent Fingerprint (IIITD-SLF). Using the proposed algorithm, the segmented images were supplied as the input image for the matching process via a state art of matcher, VeriFinger SDK. Segmentation of 240 images is performed and compared with manual segmentation methods. The results show that the proposed algorithm achieves a correct segmentation of 77.5% of the SLF images under test. 2015-04 Thesis http://umpir.ump.edu.my/id/eprint/16374/ http://umpir.ump.edu.my/id/eprint/16374/19/Image%20enhancement%20and%20segmentation%20on%20simultaneous%20latent%20fingerprint%20detection.pdf pdf en public masters Universiti Malaysia Pahang Faculty of Computer Systems & Software Engineering
institution	Universiti Malaysia Pahang Al-Sultan Abdullah
collection	UMPSA Institutional Repository
language	English
topic	QA75 Electronic computers Computer science T Technology (General)
spellingShingle	QA75 Electronic computers Computer science T Technology (General) Rozita, Mohd Yusof Image enhancement and segmentation on simultaneous latent fingerprint detection
description	A simultaneous latent fingerprint (SLF) image consists of multi-print of individual fingerprints that is lifted from a surface, typically at the crime scenes. Due to the nature and the poor quality of latent fingerprint image, segmentation becomes an important and very challenging task. This thesis presents an algorithm to segment individual fingerprints for SLF image. The algorithm aim to separate the fingerprint region of interest from image background, which identifies the distal phalanx portion of each finger that appears in SLF image. The algorithm utilizes ridge orientation and frequency features based on block-wise pixels. A combination of Gabor Filter and Fourier transform is implemented in the normalization stage. In the pre-processing stage, a modified version of Histogram equalization is proposed known as Alteration Histogram Equalization (AltHE). Sliding windows are applied to create bounding boxes in order to find out the distal phalanges region at the segmentation stage. To verify the capability of the proposed segmentation algorithm, the segmentation results is evaluated in two aspects: a comparison with the ground truth foreground and matching performance based on segmented region. The ground truth foreground refers to the manual mark up region of interest area. In order to evaluate the performance of this method, experiments are performed on the Indian Institute of Information Technology Database- Simultaneous Latent Fingerprint (IIITD-SLF). Using the proposed algorithm, the segmented images were supplied as the input image for the matching process via a state art of matcher, VeriFinger SDK. Segmentation of 240 images is performed and compared with manual segmentation methods. The results show that the proposed algorithm achieves a correct segmentation of 77.5% of the SLF images under test.
format	Thesis
qualification_level	Master's degree
author	Rozita, Mohd Yusof
author_facet	Rozita, Mohd Yusof
author_sort	Rozita, Mohd Yusof
title	Image enhancement and segmentation on simultaneous latent fingerprint detection
title_short	Image enhancement and segmentation on simultaneous latent fingerprint detection
title_full	Image enhancement and segmentation on simultaneous latent fingerprint detection
title_fullStr	Image enhancement and segmentation on simultaneous latent fingerprint detection
title_full_unstemmed	Image enhancement and segmentation on simultaneous latent fingerprint detection
title_sort	image enhancement and segmentation on simultaneous latent fingerprint detection
granting_institution	Universiti Malaysia Pahang
granting_department	Faculty of Computer Systems & Software Engineering
publishDate	2015
url	http://umpir.ump.edu.my/id/eprint/16374/19/Image%20enhancement%20and%20segmentation%20on%20simultaneous%20latent%20fingerprint%20detection.pdf
_version_	1783732009938452480

Image enhancement and segmentation on simultaneous latent fingerprint detection

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