Abstract
Nowadays, Palm vein biometric is one of the emerging techniques to build up a well-organized recognition system. This paper focuses on quality-based palm vein detection. To recognize hand palm vein images, Local Gabor Vein Code Pattern (LGVCP) is proposed. It comprises of three modules, namely Preprocessing, LGVCP and Palm Vein matching. Preprocessing is performed using Otsu thresholding method and Contrast Limited Adaptive Histogram Equalization (CLAHE) techniques. Palm vein features are extracted by applying LGVCP and Histogram of Oriented Gradients (HOG). Chi-square distance and Euclidian distance values are applied for palm vein matching. Experiments are performed on CASIA Palm vein Image database. The performance of the proposed method is evaluated by metrics, namely accuracy, specificity, sensitivity, error rate, recall and precision. The proposed method provides an accuracy of 99.001% compared to the existing ones.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal of Innovative Technology and Exploring Engineering
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
