In this blog post, we will explore the physiological characteristics of fingerprints, how fingerprint recognition systems work, and why fingerprints are widely used in security technology.
Fingerprints are raised patterns on the skin of the fingers, formed by sweat glands protruding from the dermis and creating a series of ridges and valleys. Fingerprints do not change throughout a person’s lifetime as long as the dermis remains intact. For this reason, fingerprints are widely used as important biometric information for identity verification, along with irises, veins, and voices. Each finger has a unique pattern, which is very effective in distinguishing the identity of individuals.
A fingerprint recognition system is a biometric identification system that verifies identity by determining whether a registered fingerprint matches a fingerprint being scanned. In order to register or scan a fingerprint, an image of the fingerprint must be obtained through a fingerprint input device that clearly shows the ridges and valleys of the fingerprint. The fingerprint input device obtains information through contact with the finger, at which point the ridges of the fingerprint come into contact with the contact surface, but the valleys do not. Therefore, differences occur in physical quantities such as light intensity, charge, and temperature corresponding to the ridges and valleys of the fingerprint input device.
Optical fingerprint input devices consist of a lighting device, a prism, and an image sensor. When a finger is placed on the reflective surface of the prism, moisture and oil on the ridges form a thin film on the reflective surface. The light emitted from the illumination device and incident on the thin film is refracted or scattered and reaches the image sensor in a weakened state. Since the ridges do not touch the reflective surface, the light is not refracted or scattered and is reflected to the sensor. The image sensor converts the light intensity into a digital signal to create an image of the fingerprint. This device has difficulty obtaining a complete fingerprint image when the fingerprint is dry with little sweat or oil.
Capacitive sensor-type fingerprint input devices use a plate with a dense array of microscopic capacitive sensors. Electricity flows through this plate, and each sensor is charged with a constant amount of electricity. When a finger touches the plate, the electricity is discharged, and the amount of electricity in the sensor decreases. At this point, there is a difference in the amount of charge between the sensors that have come into contact with the ridges and those that have not. The amount of charge on each sensor is converted to obtain a fingerprint image.
Superconducting sensor-type fingerprint input devices use multiple small superconducting sensors that detect changes in the temperature of the human body, arranged in a row corresponding to the width of a finger. These sensors have the characteristic of generating a signal only when the temperature changes. When a finger is moved while touching the sensors in a direction perpendicular to the direction in which they are lined up, frictional heat is generated between the contact surface and the ridges of the fingerprint, causing the temperature of the sensors to vary depending on the ridges and valleys. The sensors detect the minute temperature changes that occur at this time, convert them into corresponding signals, and store them continuously to obtain a fingerprint image. This device can be made smaller than other fingerprint input devices and can be installed in small devices such as smartphones.
In general, biometric recognition systems undergo the processes of “biometric information collection,” “preprocessing,” “feature data extraction,” and “matching,” and fingerprint recognition systems follow the same process. The biometric information collection stage is the process of obtaining fingerprint images using a fingerprint input device. In the preprocessing stage, image information unrelated to the fingerprint shape is removed, and the fingerprint images are corrected so that the characteristics of the fingerprint shape are highlighted. During this process, noise is removed and image quality is improved. In the feature data extraction stage, unique feature data for each fingerprint is extracted from the images corrected in the preprocessing stage. Feature data includes the distribution type of ridges, the location of ridges, and the connection status. In the matching stage, the feature data extracted for fingerprint search is compared with the feature data registered in advance to calculate the similarity. If this value is greater than the reference value, the fingerprint is determined to be from the same person.
Fingerprint recognition technology plays an important role in enhancing security. It is used in various fields such as banks, airports, and smartphones, and offers high accuracy and convenience. However, fingerprint recognition systems are not perfect. Errors can occur in certain environments, and there are various attempts to evade or deceive fingerprint recognition. Therefore, fingerprint recognition technology must be used in conjunction with other security measures, and continuous research and improvement are necessary.
Fingerprint recognition systems will continue to be an important biometric technology in the future, and with technological advances, they will become more sophisticated and reliable. We look forward to further improvements in the accuracy and security of fingerprint recognition through various research and development efforts.
