Method of performing fingerprint matching

A computer-implemented method of performing fingerprint matching, comprising the steps of:

• acquiring a first fingerprint image;
• locating a reference core point within the first fingerprint image in order to initiate feature extraction of the first fingerprint image;
• establishing a region of interest (ROI) around the reference core point;
• decomposing the region of interest into eight separate directional sub-band outputs;
• calculating translation, rotation, and scaling (TRS) independent moment invariants and affine moment invariants from each of the eight separate directional sub-band outputs by:
• calculating at least one geometric moment invariant Mpq, said geometric moment invariant calculation being defined by the relation Mpq=∫−∞∞∫−∞∞xpyqf(x,y)dxdy for p, q=0, 1, 2, . . . , n, where n represents a number of stored template features, x and y are Cartesian coordinates, and f(x,y) is a continuous function;
• adapting the geometric moment invariant calculation to grayscale images having pixel intensities I(x,y), the geometric moment invariant calculation adaptation being characterized by the relation MIj=ΣxΣyxIyjI(x,y) for I,j=0, 1, 2, . . . , n;
• calculating at least one complex moment invariant cpq, the complex moment invariant calculation being defined by the relation cpq=∫−∞∞∫−∞∞(x+iy)p(x−iy)qf(x,y)dxdy, where i is the complex number, the at least one complex moment invariant being based on a polynomial basis kpqcharacterized by the relation kpq(x,y)=(x+iy)p(x−iy)q;
• and
• calculating at least one orthogonal moment vpq, the orthogonal moment invariant calculation being defined by the relation vpq=npnq∫∫Ωpp(x)pq(y)f(x,y)dxdy, wherein npand nq are normalized factors and Ω is an area of orthogonality, the grayscale image being scaled such that its support is contained in Ω;
• combining features calculated from each of the separate directional sub-band outputs into a first feature vector Vf characterized by the relation Vf={Iθ1, Iθ2, . . . , Iθk}, where θε{0, 1, 2, 3, 4, 5, 6, 7}, corresponding to the eight separate directional sub-band outputs, k ε{0, 1, 2, . . . , 56}, corresponding to the independent moment invariants from each of the eight separate directional sub-band outputs, and Iθkis a feature sub-block of the θ-th directional sub-band and the k-th independent moment invariant;
• calculating an absolute distance between the first feature vector and a second vector Vf2including features of a second fingerprint having similarly obtained moment invariants, the second vector being characterized by the relation Vf2={b1, b2, . . . , bn}, where each of the {b1, b2, . . . , bn}represent one of the n stored template features;
• and
• displaying match results based on the first and second fingerprint absolute distance calculation step.