ELIS Card Photo Validation Service
Description
The card photo validation solution was developed to validate each submitted photo against a set of business-defined requirements in near-real-time in order to eliminate rejections/RFEs for the user uploaded photos.
Detailed example
Response back to user based on the pre-defined quality checks if the uploaded photo meets USCIS requirements. Users still have the option to ignore the warnings and upload the photo.
AI / analytics pattern
Computer Vision: AI that processes and interprets visual data (e.g., images and videos).
Automation level / stage
c) Deployed – The use case is being actively authorized or utilized to support the functions or mission of an agency.
Expected benefit
Ensuring beneficiary uploaded photos meet USCIS requirements. This helps ensure photos are correct before making ID cards, saving adjudicator time and avoiding delays.
Audit / financial statement impact
This use case supports beneficiaries submitting an e-filed I-765 via myUSCIS to apply for employment authorization. These applications include a digital ID photo of the applicant, which will be printed on their Employment Authorization Document (EAD) card if the application is accepted. The use case determines whether a user-uploaded ID photo is suitable for use on an EAD card, and notifies the submitter if it detects a potential quality issue with the photo. (SEE DHS CAIO SUPER MEMO FY24) --- The AI outputs do not serve as a principal basis for a decision or action concerning a specific individual or entity that has a legal, material, binding, or similarly significant effect on that individual’s or entity’s civil rights, civil liberties or privacy, equal opportunities, or access to or the ability to apply for critical government resources or services. The AI outputs are a real-time advisory message to the submitter of the photo that it is of insufficient quality for card production at which point the submitter may choose to resubmit or not. While adjudication of EADs is not dependent on this use case, this tool enhances efficiency and customer service by minimizing the number of cards failing in production and delays related to subsequent requests for information. (SEE USCIS REQUEST FOR DHS CAIO DETERMINATION FY24)
Controls / human review
ATO: Yes; PIA: https://www.dhs.gov/publication/dhsuscispia-056-uscis-electronic-immigration-system-uscis-elis
Data needed
Initial face detection is performed by pretrained dlib embeddings as implemented in opencv. Validation tests requiring object detection (headwear and eyeglasses) is performed using custom fine-tuning from Detectron2, an open-source object detection model. Training and testing data for these object detection problems was sourced from a combination of public domain face detection datasets and USCIS production data passport photos.