SlapSeg III Evaluation
Neurotechnology's slap fingerprint segmentation algorithm has been judged by NIST as the most accurate among the SlapSeg III 2 inch category participants.
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.
There are 4 categories in the SlapSeg III evaluation:
- 2 inch are scanned images of inked tenprint card slaps. Neurotechnology evaluation results are presented below.
- 3 inch are live scan images captured using devices with a scanning surface of 3 inches. Neurotechnology plans to participate in this category.
- 5.5 inch are half palm (upper palm) live scan images. Neurotechnology plans to participate in this category.
- 8 inch are full palm live scan images. Neurotechnology plans to participate in this category.
2 Inch Category
These comments provided by Neurotechnology are based on the submission results, published on March 10, 2021.
Currently there are 6 companies participating in the evaluation. Our latest submission was Neurotechnology+0005. The submitted algorithm is available in MegaMatcher 12.1 SDK and VeriFinger 12.1 SDK.
Segmentation accuracy is measured by percentage that at least 8 fingers were segmented correctly. According to this accuracy measurement our algorithm is the most accurate among the participants. Also our algorithm is the second fastest algorithm in the 2 inch category, while the faster contender showed much worse accuracy. Overall Neurotechnology+0005 showed the best speed and accuracy combination in this category.