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Minutiae extraction: The minutia extraction stage was divided into two steps: (i) Ridge thinning (ii) Minutiae Marking.
Supposing the angle of minutiae is [alpha] (-[pi] [less than or equal to] [alpha] [less than or equal to] [pi]), direction near the sample point is [[alpha].sub.l,k]([-[pi]/2] [[less than or equal to] [alpha].sub.l,k] [less than or equal to][[pi]/2]), Frequency is [1/[w.sub.l,k], [beta].sub.l,k] =[lambda] ([[alpha].sub.l,k]-[alpha]) is [[alpha].sub.l,k] relative to [alpha] angle, and then the minutia descriptor can use the following formula:
First matching of neighborhood minutiae is carried out between the two images; if similarity is found to a satisfactory threshold, then few neighborhood minutiae are sampled and the individual minutia in the neighborhood minutiae of the users current fingerprint image and the database stored image are compared further.
Prakash, "Fingerprint Minutia Match Using Bifurcation Technique," International Journal of Computer Science & Communication Networks, Vol 2(4), 478-486, 2012.
Features extracted from minutia and giving more successful results should be sought.
In this paper, we consider two distance metrics: (i) square of Euclidean distance [d.sub.E](([x.sub.i], [y.sub.i]), ([x'.sub.j], [y'.sub.j])) = [([x.sub.i]- [x'.sub.j]).sup.2] + [([y.sub.i] - [y'.sub.j]).sup.2] (for simplicity, we still call Euclidean distance) and (ii) city block distance [d.sub.B](([x.sub.i], [y.sub.i]), ([x'.sub.j], [y'.sub.j])) = [absolute value of ([x.sub.i] - [x'.sub.y]])] + [absolute value of ([y.sub.i] - [y'.sub.y]])] However, for a given minutia belonging to [M.sup.Q], the above approach might find at least one matching result belonging to [M.sup.T], but, in fact, at most one is correct.
The minutia is detected with the help of distance map from Fig.
A computer then analyzes the picture for the minutia points--intersection points of the ridges, whorls, and valleys that form a unique pattern on each fingertip.
From mind-numbing minutia to erudite minutia to the not-so minute.
For a detected minutia, MN represents the integer identifier, MX stands for the x-pixel coordinate, MY expresses the y-pixel coordinate, and DIR serves as the direction.
This system only extracts the matching of fingerprints by using minutia scores.
[3] have shown detected spurious minutia can be more harmful to reliable AFIS performance than missed genuine one, so it is imperative to minimize the number of spurious minutia to maximal extent.