Core Technologies
Fingerprint recognition is a biometric method used to verify or identify individuals based on the distinctive characteristics of their fingerprints. The intricate ridges, bifurcations, and minutiae patterns embedded in every fingerprint form a reliable, unique identifier for each person.
At Gekonova, we transform these naturally occurring markers into secure digital credentials, enabling trusted identity authentication across a wide range of secure environments and industries.
Traditional fingerprint systems once depended on physical impressions and visual inspection. At Gekonova, we’ve replaced those outdated methods with powerful AI-driven algorithms that analyze fingerprints with speed, accuracy, and strict data privacy standards.
Instead of storing images of fingerprints, our technology isolates the fingerprint’s key structural features—such as ridge endings, core points, and bifurcations. These data points are converted into a proprietary digital template that represents the unique print without retaining any visual likeness.
Each template is encrypted using AES-256, a military-grade encryption protocol that transforms the data into a secure, unreadable form unless decrypted with the proper credentials. Even if intercepted, the encrypted template is meaningless to unauthorized users.
This secure template enables real-time 1:1 (individual match) or 1:N (database search) fingerprint authentication—seamlessly deployable on embedded systems, mobile platforms, and enterprise networks. With no raw fingerprint images stored, and with encryption built into every stage, Gekonova offers a privacy-first biometric solution you can count on.
Gekonova supports a variety of sensor technologies to ensure compatibility and performance across diverse use cases:
A long-established and robust technology, optical sensors rely on visible light to scan fingerprint ridges. When a finger is placed on the sensor surface, light is reflected off the fingerprint and captured by a CMOS or CCD image sensor. Variations in the reflected light due to the ridges and valleys create a high-contrast image, which is then converted into a digital template by our image-processing engine.
Optical sensors are durable, cost-effective, and ideal for indoor applications such as time attendance systems and building access control.
Capacitive sensors work by detecting electrical charges between the fingerprint and the sensor surface. When a finger makes contact, tiny capacitors within the sensor register differences in electrical conductivity caused by ridge versus air gap contact.
Compact and effective even on dry or oily skin, capacitive sensors are often used in smartphones and handheld devices, offering precise and fast recognition in a small form factor.
Thermal sensors detect the heat signature of a fingerprint as it touches the sensor surface. Ridges transfer heat more directly than valleys, creating a contrast in temperature. This difference is captured by a sensitive thermal array and translated into a digital map of the fingerprint.
Thermal sensors are resilient in harsh or unpredictable environments and excel at detecting live skin, making them difficult to fool with fake prints or residual impressions.
Using high-frequency sound waves, ultrasonic sensors create detailed 3D models of a fingerprint, even penetrating minor surface contaminants like sweat or dirt. These sensors emit acoustic pulses that reflect differently off the fingerprint’s ridges and pores, enabling the system to reconstruct a highly accurate depth map.
Ultrasonic recognition is considered one of the most secure and spoof-resistant methods available today—ideal for applications requiring the highest level of biometric security.
Gekonova brings years of engineering expertise and innovation to biometric security. Our fingerprint recognition systems are designed not only for performance and flexibility but also for absolute trust and data safety. Here’s why global clients rely on us:
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