Fingerprint Recognition

Fingerprint Recognition

The raised portion of a human finger leaves an impression. This is called a fingerprint. Its recognition refers to the automated method of verifying a match between two human fingerprints. Fingerprints are one of many forms of methods to identify individuals and to verify their identity.
The analysis of fingerprints matching requires the comparison of several features of the print pattern. These features include patterns, which are aggregate characteristics of ridges, and minutiae points. It is also necessary to know the structure and properties of human skin to successfully employ some of the imaging technologies.


The three basic patterns of fingerprint ridges are as follows:

  • Arch – The ridges enter from one side of the finger to rise in the center. It forms an arc, and then exit to the other side of the finger.
  • Loop – The ridges enter from one side of a finger to form a curve, and then exit to that same side.
  • Whorl – Ridges form circles around a central point on the finger.

Scientists have found that family members often share the same fingerprint pattern. It leads to the belief that these patterns are inherited.

Processing Steps:

It has three primary functions like enrollment, searching and verification. Enrollment captures fingerprint image from the sensor. The reason is the way people put their fingerprints on a mirror to scan can affect the result in the searching and verifying process.
The verifying process involves several techniques like correlation-based matching, minutiae-based matching, and ridge feature-based matching.
Minutiae based matching has efficiency as well as accuracy. The features are ridge ending, bifurcation, and short ridge. The ridge ending is where a ridge terminates. The point at which a single ridge splits into two ridges, is called bifurcation. Short ridges are shorter than the average ridge length.
Minutiae and patterns are very important in the analysis of fingerprints since no two fingers have been shown to be identical.

Sensor Help:

A fingerprint sensor is used for matching. It captures a digital image of the fingerprint pattern. This captured image is digitally processed to create a biometric template. This template is used for matching. Many technologies have been used but optical, capacitive, and ultrasonic are more common.


Optical fingerprint imaging captures a digital image of the print. This type of sensor is a specialized digital camera.


Ultrasonic sensors create visual images of the fingerprint. They use very high frequency sound waves to penetrate the epidermal layer of skin. As the dermal skin layer displays the same pattern as of the fingerprint, the reflected wave measurements can be used to form a fingerprint image. LeEco introduced this technology in Smartphone. The principles of medical ultrasonography are used here.


Capacitance sensors form fingerprint images by using the sensor array pixels. Each pixel acts as one plate of a parallel-plate capacitor. The electrically conductive dermal layer acts as the other plate. The non-conductive epidermal layer acts as a dielectric. Apple used a capacitance fingerprint sensor in Touch ID.

Algorithm for Verification:

Algorithm is a program that has a sequence of commands. They can do calculation, data processing and provide probable answers. Therefore, matching algorithms are used to compare previously stored templates of fingerprints against current template. To do this, the stored original template must be directly compared with the current template. Some features can also be compared alternatively.
The edge detection quality of the image was greatly enhanced by filtering and removing noises.

Pattern based algorithm:

A comparison between a previously stored template and the current fingerprint image can be made using pattern based algorithms to determine the matching percentage. Here, the images can be aligned in the same orientation. To do this, the algorithm finds a central point in the stored image to center on that.

Fingerprint in Mobile phones:

Motorola and Apple were the earliest smartphone manufacturers to integrate fingerprint recognition into their phones. HTC, Samsung and later OPPO introduced this feature in their phones.


Fingerprint technology is coming up fast as the most widely used technology. It provides a high level of recognition accuracy. Its application range is growing day by day for example, electronic commerce, physical access, PC logon, and criminal applications.
However, factors like finger injuries may prevent certain users to use a fingerprint-based recognition system, either temporarily or permanently.

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