A Review of Fingerprint Sensors: Mechanism, Characteristics, and Applications

Identification technology based on biometrics is a branch of research that employs the unique individual traits of humans to authenticate identity, which is the most secure method of identification based on its exceptional high dependability and stability of human biometrics. Common biometric identifiers include fingerprints, irises, and facial sounds, among others. In the realm of biometric recognition, fingerprint recognition has gained success with its convenient operation and fast identif ication speed. Different fingerprint collecting techniques, which supply fingerprint information for fingerprint identification systems, have attracted a significant deal of interest in authentication technology regarding fingerprint identification systems. This work presents several fingerprint acquisition techniques, such as optical capacitive and ultrasonic, and analyzes acquisition types and structures. In addition, the pros and drawbacks of various sensor types, as well as the limits and benefits of optical, capacitive, and ultrasonic kinds, are discussed. It is the necessary stage for the application of the Internet of Things (IoT).

Multi-Wavelength Biometric Acquisition System Utilizing Finger Vasculature NIR Imaging

Personal identification using analysis of the internal and external characteristics of the human finger is currently an intensively developed topic. The work in this field concerns new methods of feature extraction and image analysis, mainly using modern artificial intelligence algorithms. However, the quality of the data and the way in which it is obtained determines equally the effectiveness of identification. In this article, we present a novel device for extracting vision data from the internal as well as external structures of the human finger. We use spatially selective backlight consisting of NIR diodes of three wavelengths. The fast image acquisition allows for insight into the pulse waveform. Thanks to the external illuminator, images of the skin folds of the finger are acquired as well. This rich collection of images is expected to significantly enhance identification capabilities using existing and future classic and AI-based computer vision techniques. Sample data from our device, before and after data processing, have been shared in a publicly available database.

Three-Dimensional Finger Vein Recognition: A Novel Mirror-Based Imaging Device

Finger vein recognition has evolved into a major biometric trait in recent years. Despite various improvements in recognition accuracy and usability, finger vein recognition is still far from being perfect as it suffers from low-contrast images and other imaging artefacts. Three-dimensional or multi-perspective finger vein recognition technology provides a way to tackle some of the current problems, especially finger misplacement and rotations. In this work we present a novel multi-perspective finger vein capturing device that is based on mirrors, in contrast to most of the existing devices, which are usually based on multiple cameras. This new device only uses a single camera, a single illumination module and several mirrors to capture the finger at different rotational angles. To derive the need for this new device, we at first summarise the state of the art in multi-perspective finger vein recognition and identify the potential problems and shortcomings of the current devices.