The Use of Two Transform Methods in Fingerprints Recognition
Finger prints are the oldest and most widely used form of biometric identification. Despite the widespread use of fingerprints, there is little statistical theory on the uniqueness of fingerprint minutiae. Fingerprint matching is the process used to determine whether two sets of fingerprint ridge de...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
University of Anbar
2012-12-01
|
| Series: | مجلة جامعة الانبار للعلوم الصرفة |
| Subjects: | |
| Online Access: | https://juaps.uoanbar.edu.iq/article_63367_9320ce78004f2e3beeb2963f25afd18f.pdf |
| _version_ | 1797373323282219008 |
|---|---|
| author | Baraa Tareq Hammad Khattab M. Ali Salah Sleibi Al-Rawi Ismail Taha Ahmed |
| author_facet | Baraa Tareq Hammad Khattab M. Ali Salah Sleibi Al-Rawi Ismail Taha Ahmed |
| author_sort | Baraa Tareq Hammad |
| collection | DOAJ |
| description | Finger prints are the oldest and most widely used form of biometric identification. Despite the widespread use of fingerprints, there is little statistical theory on the uniqueness of fingerprint minutiae. Fingerprint matching is the process used to determine whether two sets of fingerprint ridge detail come from the same finger. There exist multiple algorithms that do fingerprint matching in many different ways. Some methods involve matching minutiae points between the two images, In this paper used median filter to enhance the images, and then use DCT (Discrete Cosine Transform) and FDCvT Via Wrapping to compute the feature extraction from the images. The Template Matching can be applied by finding the more similar values between the original image and the template.The proposed system includes two stages: first stage is implemented by taking individual natural fingerprint images with several positions and calculation of the features vector (Mean and standard deviation) by using FDCvT via Wrapping and DCT. The second stage is implemented by taking several samples of new fingerprint images for testing the work. The results show that the fingerprints Recognition rate by the (FDCvT via Wrapping and DCT) achieves better recognition rate (84%). |
| first_indexed | 2024-03-08T18:47:44Z |
| format | Article |
| id | doaj.art-28570dc225864662a29ed80caf401502 |
| institution | Directory Open Access Journal |
| issn | 1991-8941 2706-6703 |
| language | English |
| last_indexed | 2024-03-08T18:47:44Z |
| publishDate | 2012-12-01 |
| publisher | University of Anbar |
| record_format | Article |
| series | مجلة جامعة الانبار للعلوم الصرفة |
| spelling | doaj.art-28570dc225864662a29ed80caf4015022023-12-28T21:56:09ZengUniversity of Anbarمجلة جامعة الانبار للعلوم الصرفة1991-89412706-67032012-12-016210110810.37652/juaps.2012.6336763367The Use of Two Transform Methods in Fingerprints RecognitionBaraa Tareq Hammad0Khattab M. Ali1Salah Sleibi Al-Rawi2Ismail Taha Ahmed3University of Anbar - College of ComputerAnbar University - College of ComputersAnbar University - College of ComputersAnbar University - College of ComputersFinger prints are the oldest and most widely used form of biometric identification. Despite the widespread use of fingerprints, there is little statistical theory on the uniqueness of fingerprint minutiae. Fingerprint matching is the process used to determine whether two sets of fingerprint ridge detail come from the same finger. There exist multiple algorithms that do fingerprint matching in many different ways. Some methods involve matching minutiae points between the two images, In this paper used median filter to enhance the images, and then use DCT (Discrete Cosine Transform) and FDCvT Via Wrapping to compute the feature extraction from the images. The Template Matching can be applied by finding the more similar values between the original image and the template.The proposed system includes two stages: first stage is implemented by taking individual natural fingerprint images with several positions and calculation of the features vector (Mean and standard deviation) by using FDCvT via Wrapping and DCT. The second stage is implemented by taking several samples of new fingerprint images for testing the work. The results show that the fingerprints Recognition rate by the (FDCvT via Wrapping and DCT) achieves better recognition rate (84%).https://juaps.uoanbar.edu.iq/article_63367_9320ce78004f2e3beeb2963f25afd18f.pdffingerprint recognitiondctcurvelet transformfdcvt via wrapping |
| spellingShingle | Baraa Tareq Hammad Khattab M. Ali Salah Sleibi Al-Rawi Ismail Taha Ahmed The Use of Two Transform Methods in Fingerprints Recognition مجلة جامعة الانبار للعلوم الصرفة fingerprint recognition dct curvelet transform fdcvt via wrapping |
| title | The Use of Two Transform Methods in Fingerprints Recognition |
| title_full | The Use of Two Transform Methods in Fingerprints Recognition |
| title_fullStr | The Use of Two Transform Methods in Fingerprints Recognition |
| title_full_unstemmed | The Use of Two Transform Methods in Fingerprints Recognition |
| title_short | The Use of Two Transform Methods in Fingerprints Recognition |
| title_sort | use of two transform methods in fingerprints recognition |
| topic | fingerprint recognition dct curvelet transform fdcvt via wrapping |
| url | https://juaps.uoanbar.edu.iq/article_63367_9320ce78004f2e3beeb2963f25afd18f.pdf |
| work_keys_str_mv | AT baraatareqhammad theuseoftwotransformmethodsinfingerprintsrecognition AT khattabmali theuseoftwotransformmethodsinfingerprintsrecognition AT salahsleibialrawi theuseoftwotransformmethodsinfingerprintsrecognition AT ismailtahaahmed theuseoftwotransformmethodsinfingerprintsrecognition AT baraatareqhammad useoftwotransformmethodsinfingerprintsrecognition AT khattabmali useoftwotransformmethodsinfingerprintsrecognition AT salahsleibialrawi useoftwotransformmethodsinfingerprintsrecognition AT ismailtahaahmed useoftwotransformmethodsinfingerprintsrecognition |