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Reference TypeConference Proceedings
Last Update2010:
Metadata Last Update2010:
Citation KeyClimentBlanHexs:2010:ApStMa
TitleApproximate string matching for iris recognition by means of boosted Gabor wavelets
FormatPrinted, On-line.
DateAug. 30 - Sep. 3, 2010
Access Date2020, Dec. 03
Number of Files1
Size436 KiB
Context area
Author1 Climent, Joan
2 Blanco, Juan Diego
3 Hexsel, Roberto
Affiliation1 Universitat Politècnica de Catalunya
2 Universitat Politècnica de Catalunya
3 Universidade Federal do Paraná
EditorBellon, Olga
Esperança, Claudio
Conference NameConference on Graphics, Patterns and Images, 23 (SIBGRAPI)
Conference LocationGramado
Book TitleProceedings
PublisherIEEE Computer Society
Publisher CityLos Alamitos
History2010-10-01 04:19:39 :: -> :: 2010
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Is the master or a copy?is the master
Document Stagecompleted
Content TypeExternal Contribution
Tertiary TypeFull Paper
Keywordsiris recognition, AdaBoost, biometrics, Levenshtein distance, string matching.
AbstractThis paper presents an efficient IrisCode classifier, built from phase features which uses AdaBoost for the selection of Gabor wavelets bandwidths. The final iris classifier consists of a weighted contribution of weak classifiers. As weak classifiers we use 3-split decision trees that identify a candidate based on the Levenshtein distance between phase vectors of the respective iris images. Our experiments show that the Levenshtein distance has better discrimination in comparing IrisCodes than the Hamming distance. Our process also differs from existing methods because the wavelengths of the Gabor filters used, and their final weights in the decision function, are chosen from the robust final classifier, instead of being fixed and/or limited by the programmer, thus yielding higher iris recognition rates. A pyramidal strategy for cascading filters with increasing complexity makes the system suitable for realtime operation.
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