Which fingerprint pattern is a whorl?
Whorl, plain – A type of print pattern that consists of one or more friction ridges making a complete circuit and two deltas; an imaginary line drawn between the two deltas touches or crosses at least one recurving ridge within the inner pattern area.
What is whorl in fingerprint?
Whorls – form circular or spiral patterns, like tiny whirlpools. There are four groups of whorls: plain (concentric circles), central pocket loop (a loop with a whorl at the end), double loop (two loops that create an S-like pattern) and accidental loop (irregular shaped).
What percentage of the population have the fingerprint patterns of whorls?
Loops are the most common type of fingerprint; on average 65% of all fingerprints are loops. Approximately 30% of all fingerprints are whorls, and arches only occur about 5% of the time. There are subcategories for each of these.
How can you predict the hand of a whorl?
The same principle holds true for double loop whorl patterns. By locating the bottom loop (the loop that flows down from the core) you can predict what hand the double loop whorl most likely originated from by following the ridge flow away from the core.
How is the direction of a whorl pattern determined?
The axis most often flows to the right or left. This directional flow will accurately predict which hand the whorl originated from. Locating the axis of a whorl pattern and following the directional flow of the axis down will indicate which hand it originated from.
How is the structure of a fingerprint determined?
Structural based approach – Chong & Ngee (1997) 1. The fingerprint classification procedure is based on determining the global geometric structure of the extracted ridges using B- splines. 2. The B-splines provide a compact representation of the ridges and contain enough information to determine their geometric structure.
How does fingerprint classification reduce the search space?
Fingerprint Classification. Fingerprint classification is a coarse level partitioning of a fingerprint database into smaller subsets. Fingerprint classification reduces the search space of a large database: Determine the class of the query fingerprint. Then, only search templates with the same class as the query.