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SlapSeg III Evaluation

These comments provided by Neurotechnology are based on the submission results, reviewed on November 30, 2023.

Neurotechnology's slap fingerprint segmentation algorithm showed off as a top performer in the SlapSeg III evaluation, featuring the fastest performance and almost the best accuracy in most categories of the SlapSeg III evaluation.

What is SlapSeg III?

SlapSeg III Evaluation is a NIST-run public test of automated slap fingerprint segmentation algorithms. Output from the tested automated algorithms is compared to output from a human examiner and analyzed for similarity.

See SlapSeg III official page for more information.

Fingerprint segmentation is the act of separating or segmenting an image of the friction ridge structure of the hand into individual images of the upper-most finger joints, known as distal phalanges.

Currently there are 9 vendors participating in the evaluation. Our latest submission is Neurotechnology+0011. The submitted algorithm is available in MegaMatcher SDK and VeriFinger SDK.

Neurotechnology evaluation results in all 4 categories of the SlapSeg III are presented below:

Tenprint Cards Category

This category uses "TwoInch" scanned images of inked ten-print card slaps. Segmentation accuracy in this category is measured by the percentage that at least 8 fingers were segmented correctly.

Our algorithm is the fastest and second most accurate among this category's participants, showing:

  • 85.2% correct segmentation ratio versus 90.5% for the more accurate contender.
  • 38 ms mean combined segmentation time versus 177 ms by the more accurate contender.

Overall Neurotechnology+0011 showed the best speed and accuracy combination in this category.

Identification Flats Category

This category uses "ThreeInch" live scan images captured using devices with a 3-inch scanning surface. Segmentation accuracy in this category is measured by the percentage that all 10 fingers were segmented correctly.

Our algorithm is the fastest and fourth most accurate among this category's participants, showing:

  • 84.3% correct segmentation ratio versus 86.7% for the most accurate contender.
  • 42 ms mean combined segmentation time versus 257 ms by the most accurate contender.

Our algorithm provides the perfect balance between accuracy and speed according to the measurement, as it is significantly faster and features the correct segmentation ratio close to the more accurate contenders.

Upper Palms Category

This category uses "FiveInch" half palm (upper palm) live scan images. Segmentation accuracy in this category is measured by percentage that at least 8 fingers were segmented correctly.

Our algorithm showed :

  • 53.9% correct segmentation ratio versus 65.6% for the most accurate contender.
  • 162 ms mean combined segmentation time versus 686 ms by the most accurate contender.

Overall Neurotechnology+0011 algorithm submission showed balanced speed and accuracy combination, providing good ratio of correct segmenttations in a reasonable time.

Full Palm Category

This category uses "EightInch" full palm live scan images. Segmentation accuracy in this category is measured by percentage that at least 8 fingers were segmented correctly.

Our algorithm is the fastest and third most accurate among this category's participants, showing:

  • 89.5% correct segmentation ratio versus 96.7% for the most accurate contender.
  • 129 ms mean combined segmentation time versus 546 ms by the most accurate contender.

Overall Neurotechnology+0011 showed the best speed and accuracy combination in this category, featuring the lowest segmentation time with the correct segmentation ratio close to the more accurate contenders..

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