The purpose of this study is to test multiple face standards to determine Equal Error Rates (EER) amid the facial standard tests preformed. This study will help determine if one face sample can be interoperable amongst multiple standards. Removing facial features from a cropped image raises the EER, lowering the effectiveness of the facial recognition.

1. FACE SEGMENTATION STANDARDS
David Shatzer, Douglas Vaisnoras, Blake Rathburn, Michael Brockly, Stephen Elliott
Overview
The purpose of this study is to test multiple face standards to determine Equal Error Rates (EER) amid the facial standard tests
preformed. This study will help determine if one face sample can be interoperable amongst multiple standards. Removing facial
features from a cropped image raises the EER, lowering the effectiveness of the facial recognition.
Facial Standard Tests Performed
• UNCROPPED IMAGES
• FIND-BEST PRACTICE
• ISO-FRONTAL
• ISO-TOKEN
• TIGHT
Relevancy
• Potential international acceptance, one that
works in the U.S. will work globally
• Saves space, time and money by unifying
standards
• Multiple accepted standards
EER Defined
The equal error rate is the point where the probability of false
acceptance is equal to the probability of false verification.
EER is used as a metric because it is non-discriminating.
Standards Comparison EER Table
Analysis
The variation in the EER is due to how the matcher
analyzes the different images. Each standard except for the
TIGHT standard is the same initial images just cropped and
matched with different variables. The TIGHT standard has
a higher EER because the image is heavily zoomed in. This
makes it harder for the matcher to recognize a face
resulting in a higher EER.
UNCROPPED ISO-FRONTAL TIGHT
Conclusion
From our analysis, keeping the original image without
distorting the image results in a lower EER. When
removing facial feature from an image, the matcher has
difficulty locating the facial features. This results into a
higher EER.
Recommendations
• If one crops an image, the cropped image should not remove facial features
• Universal acceptance is challenging, however should be strived for
• If one crops an image to a standard, keep the original proportions
• When changing the image dimensions, use spacers to ensure image integrity