ROBUST WRIST VEINS ROI LOCALIZATION ALGORITHM BASED ON AN IMPROVED JOINT- ENTROPY THRESHOLDING METHOD | ||||
| Engineering Research Journal (Shoubra) | ||||
| Volume 48, Issue 1, April 2021, Page 189-203 PDF (5.94 MB) | ||||
| Document Type: Research articles | ||||
| DOI: 10.21608/erjsh.2021.404890 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
Abdelwahab Alsammak ; May Salama; Sarah Moustafa kamel 
| ||||
| Electrical Engineering Department, Faculty of Engineering at Shoubra, Benha University. | ||||
| Abstract | ||||
| Hand veins, being an inner body trait, demonstrated a reliable, secure and anti-spoofing biometric trait. Vein recognition performance highly depends on the precise detection of the vein Region-of-Interest (ROI). External influences like poor illumination, noise, blurring, complicated backgrounds, and incomplete capturing of hand region can affect the quality while capturing, causing performance degradation of wrist region segmentation that eventually leads to inaccurate ROI detection. In this paper, we propose a ROI localization method for wrist veins images. It consists of three steps: wrist region segmentation based on joint-entropy (JE) thresholding method, wrist orientation correction and ROI detection. The proposed segmentation method is compared with fifteen image segmentation methods using low quality wrist-vein images from PUT vein dataset and is evaluated by six segmentation evaluation metrics. Experiments show that the proposed method produced 99.524% accuracy that is 1.022% more accurate than the original JE thresholding method. | ||||
| Keywords | ||||
| wrist veins; image segmentation; Joint Entropy thresholding; ROI localization | ||||
|
Statistics Article View: 52 PDF Download: 56 |
||||
