Abstract
In current biometric security systems using images for security authentication, finger vein-based systems are getting special attention in particular attributable to the facts such as insurance of data confidentiality and higher accuracy. Previous studies were mostly based on finger-print, palm vein etc. however, due to being more secure than fingerprint system and due to the fact that each person's finger vein is different from others finger vein are impossible to use to do forgery as veins reside under the skin. The system that we worked on functions by recognizing vein patterns from images of fingers which are captured using near Infrared(NIR) technology. Due to the lack of an available database, we created and used our own dataset which was pre-trained using transfer learning of AlexNet model and verification is done by applying correct as well as incorrect test images. The result of deep convolutional neural network (CNN) based several experimental results are shown with training accuracy, training loss, Receiver Operating Characteristic (ROC) Curve and Area Under the Curve (AUC).
Highlights
Biometric identification-based technology has seen an outstanding growth in the recent years and among them finger vein-based identification is mention worthy due to its efficiency in providing security and accuracy [1]
Based on deep convolutional neural network (CNN) a model known as AlexNet [28] which consists of two fully-connected layers, five convolutional layers, and a softmax output layer
If the predicted result is the positive and actual result is positive it is known as the true positive (TP)
Summary
Biometric identification-based technology has seen an outstanding growth in the recent years and among them finger vein-based identification is mention worthy due to its efficiency in providing security and accuracy [1]. Finger vein-based systems have benefits in comparison to other conventional techniques since it is non-intrusive and device size is smaller. It possesses great future prospects in the biometric technology field [4]. Among other mention-worthy techniques such as Far-infrared (FIR) and Near-infrared (NIR) is able to detect finger veins accurately. NIR and FIR both camera technologies possess the capability of infiltrating 5mm under the skin tissue and illuminating 740-940 nanometers [6] whereas human eyes are only able to see in between 380-720 nanometers in the visible light spectrum [7]. FIR detects tissues with higher temperature adjacent to the outside skin while NIR captures venous networks which carries blood due to the blood having the ability to absorb infrared radiation. FIR detects tissues with higher temperature adjacent to the outside skin while NIR captures venous networks which carries blood due to the blood having the ability to absorb infrared radiation. [8]
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