Browse Prior Art Database

Fingerprint Pattern Offset Determination and Matching Method

IP.com Disclosure Number: IPCOM000081815D
Original Publication Date: 1974-Aug-01
Included in the Prior Art Database: 2005-Feb-28
Document File: 3 page(s) / 40K

Publishing Venue

IBM

Related People

Gaffney, JE: AUTHOR

Abstract

This method identifies the most likely positional offsets of one encoded fingerprint relative to another with which it is to be matched to determine the degree of coincidence of the pattern units, i.e., the minutiae which constitute them.

This text was extracted from a PDF file.
At least one non-text object (such as an image or picture) has been suppressed.
This is the abbreviated version, containing approximately 54% of the total text.

Page 1 of 3

Fingerprint Pattern Offset Determination and Matching Method

This method identifies the most likely positional offsets of one encoded fingerprint relative to another with which it is to be matched to determine the degree of coincidence of the pattern units, i.e., the minutiae which constitute them.

Two fingerprints to be compared, typically, can be located somewhat differently in the scanning aperture of a fingerprint verification apparatus. Accordingly, their encoded representations could exhibit a corresponding relative displacement, i.e., rotational and/or translational.

A typical idealized fingerprint pattern 10 is shown in Fig. 1a. Also shown are a plurality of minutiae 12 (bifurcations and line endings of the fingerprint). The object of the matching scheme employed is to compare the encoded array of "point vectors" 14 as shown in Fig. 1b. The "point vectors" are derived from the plurality of minutiae 12 in Fig. 1a. Similarly represented sets of data are stored in a large file. As shown in Fig. 1b, typical minutiae i can be represented as triplets of coordinates for x(i), y(i) and theta(i).

The problem is to geographically overlay any two arrays at the least number of possible relative displacements. The method employed consists of four basic steps:
(1) Determine the likely values of rotational

("theta" offsets of one array relative to

the other.
(2) For each of these arrays, similarly determine

possible translational ("x" and "y") offsets.
(3) The coordinates of the points of the arrays are

rotated and translated in correspondence with

each of the possible rotational and/or translational

displacements aforementioned.
(4) Determine the degree of geographical overlay for

each point in the arrays.

The first three steps are "necessary but not sufficient" to ascertain the positions of relative offsets at which the two arrays, i.e., subject array and file array, would be most likely to match if the...