Extract an Effective  Region of Interest using  Automated Thresholding for Finger Vein Biometric

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SAPNA SHARMA; Dr. Shikha Lohchab

Extract an Effective Region of Interest using Automated Thresholding for Finger Vein Biometric

Authors: SAPNA SHARMA, Dr. Shikha Lohchab

Unique Paper ID: 153759
Volume: 8
Issue: 8
PageNo: 482-488

Keywords: Edge detection Histogram Region of interest Segmentation Thresholding.

Abstract:
The development in the consumerâ€™s electronics demands for high security, accuracy and high speed of authentication. Human behavioral and physiological features in biometric have a large scope at providing solutions for security issues. Finger vein based personal authentication provides a better degree of security that protects information and control access much better. To explore the effective region from the acquired finger vein image, we proposed an identification of region of interest (ROI) based on automated thresholding. It is usually composed of finger region segmentation, image orientation correction, and ROI detection. In this paper we have used image pre-processing, batch processing and thresholding transformation concepts to extract meaningful ROI. The proposed automated thresholding to detect the ROI of the image has been studied, implemented and tested over the SDUMLA-HMT database.

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Cite This Article

ISSN: 2349-6002
Volume: 8
Issue: 8
PageNo: 482-488

Extract an Effective Region of Interest using Automated Thresholding for Finger Vein Biometric

Available:https://ijirt.org/article?manuscript=153759

24 Jan, 2022

Transfer Learning based CNN Model for Personal Authentication using Finger Vein Biometric

Impact Factor
8.01 (Year 2024)

UGC Approved
Journal no 47859

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