SERVICE

• Fingerprint image acquisitionWhen a finger presses on the fingerprint sensor, the sensor converts the fingerprint ridge information into electrical signals or other forms of signals based on its working principle, thereby generating a fingerprint image.
• Feature extractionPreprocess the collected fingerprint image, such as denoising, binarization, thinning, etc., and then extract the feature points of the fingerprint, such as endpoints, bifurcations, etc. These feature points constitute the fingerprint feature template.
• Fingerprint matching and verificationCompare the fingerprint feature template to be recognized with the fingerprint templates stored in the storage unit, calculating the similarity between the two. If the similarity reaches the set threshold, it is considered a successful match, meaning the fingerprint has been recognized; otherwise, the match fails.

• Fingerprint SensorIt is the core component of the fingerprint module, responsible for capturing fingerprint images. Common types of fingerprint sensors include optical sensors, capacitive sensors, and ultrasonic sensors. Optical sensors capture fingerprint images by reflecting light; capacitive sensors obtain fingerprint information by utilizing the capacitance changes formed between the finger and the sensor surface; ultrasonic sensors scan fingerprint patterns by emitting and receiving ultrasonic waves.
• Signal Processing CircuitIt mainly amplifies, filters, and converts the analog signals collected by the fingerprint sensor into digital signals for subsequent processing and analysis.
• Control ChipIt is responsible for coordinating the work of various parts of the fingerprint module, performing feature extraction, matching, and verification on the processed fingerprint data. It can also communicate with external devices to integrate and apply fingerprint recognition functions.
• Storage UnitIt is used to store fingerprint template data, configuration information, etc. Some fingerprint modules may also have encryption storage functions to ensure the security of fingerprint data.

• Security FieldUsed for access control systems, monitoring systems, etc. Only personnel verified by fingerprint can Enter specific areas or operate related equipment, enhancing security capabilities.
• Mobile DevicesSuch as smartphones, tablets, etc. Users can unlock devices, make payments, Sign In to applications, etc., conveniently and securely.
• Financial FieldIn scenarios such as bank self-service devices and online banking, fingerprint recognition can serve as a method of identity verification, ensuring the safety of users' funds.
• Attendance SystemOrganizations such as enterprises and schools use fingerprint modules for attendance management, recording the attendance of employees or students through fingerprint recognition, improving the accuracy and efficiency of attendance.

• Higher recognition accuracyWith the continuous advancement of technology, the recognition accuracy of fingerprint modules will continue to improve, enabling more accurate identification of various complex fingerprints, reducing false acceptance rates and false rejection rates.
• Smaller size and lower power consumptionIn order to meet the requirements for miniaturization and low power consumption in mobile devices and other applications, fingerprint modules will develop towards smaller sizes and lower power consumption to better integrate into various devices.
• Multimodal fusionBy combining with other biometric technologies (such as facial recognition, iris recognition, etc.) as well as traditional identity authentication methods like passwords and tokens, a multimodal identity authentication system is formed, providing a more secure and convenient identity verification solution.
• Enhanced security performanceBy adopting more advanced encryption technologies and secure authentication protocols, the protection of fingerprint data is strengthened to prevent security issues such as fingerprint information theft and tampering.

From the perspective of specific indicators, the optical fingerprint module has a false rejection rate (FRR) of <0.1% at security level 3. The capacitive fingerprint module has a false rejection rate (FRR) of <1.0% at the same security level. It is generally believed that the optical fingerprint module performs better in terms of false rejection rate, but under other conditions, both have their own strengths.