3DiVi Inc. Launches QAA - a Biometric Dataset Quality Check-Up Tool for Face Authentication Systems
3DiVi Inc., a leader in computer vision and facial recognition technologies, has launched its new Quality Assessment Algorithm (QAA), designed to address a critical challenge in face authentication systems—the quality of the facial images used for recognition.
Walnut, CA, February 14, 2025 --(PR.com)-- When implementing face authentication systems, banks and fintech companies often unknowingly work with datasets containing poor facial images — obscured by low lighting, bad angles, or occlusions like masks and glasses.
This leads to increased false positives (mistaking one person for another), false negatives (failing to recognize a legitimate customer), and a higher risk of fraud.
Evaluating the quality of photos before they are used in biometric systems can help mitigate these risks.
3DiVi's Quality Assessment Algorithm (QAA) automatically filters and evaluates the suitability of photos for recognition.
This results in up to a 50% reduction in facial comparison errors and up to a 40% reduction in liveness detection errors.
In situations where users attempt identification in low-light environments, wearing glasses, or with face obstructions like masks, the success rate of face recognition can drop to random levels. For this reason, it's crucial to monitor the conditions under which photos are captured, ensuring proper lighting, clear visibility of the face, and sufficient image resolution.
Long-Term Quality Control Recommendations
For ongoing improvements to biometric dataset quality, 3DiVi experts recommend:
- Full Dataset Review: Comprehensive analysis of all images.
- Bad Data Replacement: Removal or enhancement of poor-quality images.
- Continuous Quality Control: Ongoing validation to ensure the consistency of image quality.
- Environmental Adjustments: Guidelines for optimal lighting, camera positioning, and image capture techniques.
With financial fraud losses already in the billions annually, ensuring the quality of biometric data is not just a technical concern—it’s a critical business necessity. By regular photo quality checks, banks and fintech companies can reduce false positives, speed up customer verification, and significantly reduce fraud risks.
About 3DiVi Inc.
3DiVi Inc., founded in 2011, is one of the leading international developers of AI and machine learning (ML) technologies for computer vision. The company's computer vision algorithms cover face recognition, body and skeletal tracking, spatial understanding and object recognition.
For more information: https://3divi.ai/
This leads to increased false positives (mistaking one person for another), false negatives (failing to recognize a legitimate customer), and a higher risk of fraud.
Evaluating the quality of photos before they are used in biometric systems can help mitigate these risks.
3DiVi's Quality Assessment Algorithm (QAA) automatically filters and evaluates the suitability of photos for recognition.
This results in up to a 50% reduction in facial comparison errors and up to a 40% reduction in liveness detection errors.
In situations where users attempt identification in low-light environments, wearing glasses, or with face obstructions like masks, the success rate of face recognition can drop to random levels. For this reason, it's crucial to monitor the conditions under which photos are captured, ensuring proper lighting, clear visibility of the face, and sufficient image resolution.
Long-Term Quality Control Recommendations
For ongoing improvements to biometric dataset quality, 3DiVi experts recommend:
- Full Dataset Review: Comprehensive analysis of all images.
- Bad Data Replacement: Removal or enhancement of poor-quality images.
- Continuous Quality Control: Ongoing validation to ensure the consistency of image quality.
- Environmental Adjustments: Guidelines for optimal lighting, camera positioning, and image capture techniques.
With financial fraud losses already in the billions annually, ensuring the quality of biometric data is not just a technical concern—it’s a critical business necessity. By regular photo quality checks, banks and fintech companies can reduce false positives, speed up customer verification, and significantly reduce fraud risks.
About 3DiVi Inc.
3DiVi Inc., founded in 2011, is one of the leading international developers of AI and machine learning (ML) technologies for computer vision. The company's computer vision algorithms cover face recognition, body and skeletal tracking, spatial understanding and object recognition.
For more information: https://3divi.ai/
Contact
3DiVi Inc.
David Mitchell
+1 408 462 2760
3divi.ai
David Mitchell
+1 408 462 2760
3divi.ai
Contact
Categories