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Finger-knuckle-print image enhancement based on brightness preserving dynamic fuzzy histogram equalization and filtering process.

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Title: Finger-knuckle-print image enhancement based on brightness preserving dynamic fuzzy histogram equalization and filtering process.
Authors: Hajri, Sarra1 hajrisarra@gmail.com, Kallel, Fathi2, Hamida, Ahmed Ben2, Nait-Ali, Amine1,2
Source: Journal of Electronic Imaging. May/Jun2018, Vol. 27 Issue 3, p1-8. 8p.
Subjects: Histograms, Image segmentation, Digital image processing, Fuzzy algorithms, Image analysis
Abstract: Finger-knuckle-print (FKP) is considered as one of the emerging hand biometric traits due to its potentiality toward the identification of individuals. However, extracting features out of poor contrast FKP images is the most challenging problem faced in this area. We propose a method for personal recognition using FKP images based on a preprocessing step to improve the contrast of input FKP image and a processing step for features extraction. In the first part, we compared the performances of different histogram equalization-based contrast enhancement algorithms. The enhanced image with better performance is considered in a second step for feature extraction and personal identification. We experimentally compared the proposed approach to other existing approaches in literature using PolyU FKP database framework, and results show that our technique performed favorably. ©2018 SPIE and IS&T [DOI: 10.1117/1.JEI.27.3.033035] [ABSTRACT FROM AUTHOR]
Copyright of Journal of Electronic Imaging is the property of SPIE - International Society of Optical Engineering and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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DbLabel: Engineering Source
An: 130882639
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PubType: Academic Journal
PubTypeId: academicJournal
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  Data: Finger-knuckle-print image enhancement based on brightness preserving dynamic fuzzy histogram equalization and filtering process.
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  Data: <searchLink fieldCode="AR" term="%22Hajri%2C+Sarra%22">Hajri, Sarra</searchLink><relatesTo>1</relatesTo><i> hajrisarra@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Kallel%2C+Fathi%22">Kallel, Fathi</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Hamida%2C+Ahmed+Ben%22">Hamida, Ahmed Ben</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Nait-Ali%2C+Amine%22">Nait-Ali, Amine</searchLink><relatesTo>1,2</relatesTo>
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Electronic+Imaging%22">Journal of Electronic Imaging</searchLink>. May/Jun2018, Vol. 27 Issue 3, p1-8. 8p.
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  Data: <searchLink fieldCode="DE" term="%22Histograms%22">Histograms</searchLink><br /><searchLink fieldCode="DE" term="%22Image+segmentation%22">Image segmentation</searchLink><br /><searchLink fieldCode="DE" term="%22Digital+image+processing%22">Digital image processing</searchLink><br /><searchLink fieldCode="DE" term="%22Fuzzy+algorithms%22">Fuzzy algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Image+analysis%22">Image analysis</searchLink>
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  Data: Finger-knuckle-print (FKP) is considered as one of the emerging hand biometric traits due to its potentiality toward the identification of individuals. However, extracting features out of poor contrast FKP images is the most challenging problem faced in this area. We propose a method for personal recognition using FKP images based on a preprocessing step to improve the contrast of input FKP image and a processing step for features extraction. In the first part, we compared the performances of different histogram equalization-based contrast enhancement algorithms. The enhanced image with better performance is considered in a second step for feature extraction and personal identification. We experimentally compared the proposed approach to other existing approaches in literature using PolyU FKP database framework, and results show that our technique performed favorably. ©2018 SPIE and IS&T [DOI: 10.1117/1.JEI.27.3.033035] [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Journal of Electronic Imaging is the property of SPIE - International Society of Optical Engineering and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1117/1.JEI.27.3.033035
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        Text: English
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        Type: general
      – SubjectFull: Image segmentation
        Type: general
      – SubjectFull: Digital image processing
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      – SubjectFull: Fuzzy algorithms
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      – SubjectFull: Image analysis
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      – TitleFull: Finger-knuckle-print image enhancement based on brightness preserving dynamic fuzzy histogram equalization and filtering process.
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              M: 05
              Text: May/Jun2018
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              Y: 2018
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