ResearchSpace

A comparative study of fingerprint thinning algorithms

Show simple item record

dc.contributor.author Khanyile, NP
dc.contributor.author Tapamo, JR
dc.contributor.author Dube, E
dc.date.accessioned 2012-04-13T12:38:09Z
dc.date.available 2012-04-13T12:38:09Z
dc.date.issued 2011-08
dc.identifier.citation Khanyile, NP, Tapamo, JR and Dube, E. A comparative study of fingerprint thinning algorithms. 10th Annual Information Security for South Africa Conference (ISSA 2011), Hayatt Regency Hotel, Rosebank, South Africa, 15-17 August 2011 en_US
dc.identifier.isbn 978-1-4577-1482-5
dc.identifier.uri http://icsa.cs.up.ac.za/issa/2011/Proceedings/Research/Khanyile_Tapamo_Dube.pdf
dc.identifier.uri http://hdl.handle.net/10204/5755
dc.description Copyright: 2011 IEEE. This is the post-print version of the work. Reprinted, with permission, from Khanyile, NP, Tapamo, JR and Dube, E. A comparative study of fingerprint thinning algorithms. 10th Annual Information Security for South Africa Conference (ISSA 2011), Hayatt Regency Hotel, Rosebank, South Africa, 15-17 August 2011. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of CSIR Information Services' products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it. en_US
dc.description.abstract Thinning plays a very important role in the preprocessing phase of automatic fingerprint recognition/identification systems. The performance of minutiae extraction relies heavily on the quality of skeletons used. A good fingerprint thinning algorithm can depress image noise and promote the robustness of the minutiae extraction algorithm which helps improve the overall performance of the system. Many thinning algorithms have been devised and applied to a wide range of applications including, Optical Character Recognition (OCR), biological cell structures and fingerprint patterns. With so many thinning algorithms available, deciding which one is appropriate for a particular application has become very difficult. In an effort to assist fingerprint biometrics developers choose an appropriate thinning algorithm, a study was taken to compare performance of four different thinning algorithms. These four algorithms are implemented and their performance evaluated and compared. The algorithms are compared in terms of the quality of the skeletons they produce (i.e. connectivity and spurious branches) as well as the time complexity associated with each algorithm. Results show that faster algorithms have difficulty preserving connectivity. Zhang and Suen’s algorithm gives the least processing time, while Guo and Hall’s algorithm produces the best skeleton quality. en_US
dc.language.iso en en_US
dc.publisher IEEE en_US
dc.relation.ispartofseries Workflow;8415
dc.subject Fingerprint Recognition en_US
dc.subject Fingerprint thinning algorithms en_US
dc.subject Biometrics en_US
dc.subject Optical Character Recognition en_US
dc.subject OCR en_US
dc.title A comparative study of fingerprint thinning algorithms en_US
dc.type Conference Presentation en_US
dc.identifier.apacitation Khanyile, N., Tapamo, J., & Dube, E. (2011). A comparative study of fingerprint thinning algorithms. IEEE. http://hdl.handle.net/10204/5755 en_ZA
dc.identifier.chicagocitation Khanyile, NP, JR Tapamo, and E Dube. "A comparative study of fingerprint thinning algorithms." (2011): http://hdl.handle.net/10204/5755 en_ZA
dc.identifier.vancouvercitation Khanyile N, Tapamo J, Dube E, A comparative study of fingerprint thinning algorithms; IEEE; 2011. http://hdl.handle.net/10204/5755 . en_ZA
dc.identifier.ris TY - Conference Presentation AU - Khanyile, NP AU - Tapamo, JR AU - Dube, E AB - Thinning plays a very important role in the preprocessing phase of automatic fingerprint recognition/identification systems. The performance of minutiae extraction relies heavily on the quality of skeletons used. A good fingerprint thinning algorithm can depress image noise and promote the robustness of the minutiae extraction algorithm which helps improve the overall performance of the system. Many thinning algorithms have been devised and applied to a wide range of applications including, Optical Character Recognition (OCR), biological cell structures and fingerprint patterns. With so many thinning algorithms available, deciding which one is appropriate for a particular application has become very difficult. In an effort to assist fingerprint biometrics developers choose an appropriate thinning algorithm, a study was taken to compare performance of four different thinning algorithms. These four algorithms are implemented and their performance evaluated and compared. The algorithms are compared in terms of the quality of the skeletons they produce (i.e. connectivity and spurious branches) as well as the time complexity associated with each algorithm. Results show that faster algorithms have difficulty preserving connectivity. Zhang and Suen’s algorithm gives the least processing time, while Guo and Hall’s algorithm produces the best skeleton quality. DA - 2011-08 DB - ResearchSpace DP - CSIR KW - Fingerprint Recognition KW - Fingerprint thinning algorithms KW - Biometrics KW - Optical Character Recognition KW - OCR LK - https://researchspace.csir.co.za PY - 2011 SM - 978-1-4577-1482-5 T1 - A comparative study of fingerprint thinning algorithms TI - A comparative study of fingerprint thinning algorithms UR - http://hdl.handle.net/10204/5755 ER - en_ZA


Files in this item

This item appears in the following Collection(s)

Show simple item record