Palm Vein Detection Based on Local Gabor Vein Code Pattern and Hog
N. Subathra1, K. Merriliance2
1N.Subathra, Research Scholar, Department of Computer Science, Manonmaniam Sundaranar University, Tirunelveli, Tamil Nadu, India.
2Dr.K.Merriliance, Associate Professor, Department of Computer Applications,Sarah Tucker College (Autonomous), Tirunelveli, Tamilnadu, India.
Manuscript received on January 15, 2020. | Revised Manuscript received on January 21, 2020. | Manuscript published on February 10, 2020. | PP: 785-890 | Volume-9 Issue-4, February 2020. | Retrieval Number: C8929019320/2020©BEIESP | DOI: 10.35940/ijitee.C8929.029420
Open Access | Ethics and Policies | Cite | Mendeley
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
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.
Keywords: Palm Vein, OTSU, LGVCP, ROI,CLAHE,HOG
Scope of the Article: Image Processing and Pattern Recognition