ICAO check (International Civil Aviation Organization) is a feature that allows you to verify the compliance of a government-issued ID (e.g. passport, driver’s license, national ID card) with the standards set by the International Civil Aviation Organization (ICAO). This can be useful in a variety of scenarios, such as access control, financial transactions, and online authentication.
How it works:
The ICAO check feature uses machine learning algorithms to analyze the ID card and check if it meets the technical and security standards set by the ICAO, such as the format of the MRZ (Machine Readable Zone) and the security features of the document. The system then generates a compliance score, indicating the level of confidence that the ID card is compliant with the ICAO standards.
How to use it:
To use the ICAO check feature, you will need to have access to a government-issued ID card and the software that performs the compliance check. The user will need to present their ID card, and the software will then analyze the document and generate a compliance score. Depending on the specific implementation, the system may also have a user interface that allows you to review the compliance check and make a final decision.
Benefits of ICAO Check
Meet Regulatory Compliance
By ensuring that the ID card is compliant with the ICAO standards, you can ensure that the person is who they claim to be, which can help to prevent fraud and other types of identity-related crimes.
Convenience
ICAO check eliminates the need for manual verification of ID documents, which can save time and reduce errors.
Automation
ICAO check can be integrated into automated systems such as access control, e-commerce, and online transactions, which can improve
Metrics
Estimate Pose
Returns the estimated position of the head which is useful information to check if the face is facing the camera. Returns the float array of values which are the yaw, roll and pitch position. Examples:(128, 180, 78).
Hat detector
Determine whether an image contains hat or not using an ML model. It returns a float value.
HeadinFrame
This metric checks if the head is inside the portrait capture i.e the head of the person is not cut off or the side of the face cut off. Returns a boolean value i.e True or False.
Blur detector
Determine whether an image is blur or not using an ML model. It returns a float value. Note: the difference between this and Focus Blur is that this was built with machine learning model.
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