FIG. 1 shows, schematically, individual steps of the method in accordance with the invention.
FIG. 2 shows the size of a tile to be filtered at different phases of the method in accordance with the invention.
FIG. 3 shows an example of a fingerprint image
FIG. 4 shows a Gabor filter in perspective view.
FIG. 1 shows the Gabor filtration of a tile 1 of a fingerprint image, wherein, owing to the regulations for patent drawings, the effect of the filtration itself is not shown. Tile 1 is one part of the fingerprint as shown in FIG. 3, and may have, for example, 32×32 image elements. However, other sizes and non-quadratic, square tiles are also possible. With the known Gabor filtration, a two-dimensional filtration, in which the Gabor filter is aligned according to the bars 2 running obliquely and in a curve, would have to take place in the example shown in FIG. 1.
In the method in accordance with the invention, however, the mean direction of the bars is determined with algorithms that are known per se, whereupon tile 1 is rotated in such a way that the mean direction of the bars 2 is located at a right angle. The thus rotated tile 3 is filtered with a filter 4 comprising a cosine finction modulated with a Gaussian bell- shaped curve. The frequency of the cosine function is matched, in advance, to the spatial frequency of the bars 2. The width of the Gaussian bell-shaped curve depends on the curvature of the bars and, if applicable, on the change in spatial frequency of the bars.
In a further step, the initially one-dimensionally filtered, rotated tile is filtered at a right angle to the previous filtration with a Gaussian bell-shaped curve 5. The width of this Gaussian bell-shaped curve depends on the mean curvature of the bars 2. Subsequently, the two-dimensionally filtered tile 3′ is rotated back to its starting position.
FIG. 2 illustrates that, in order to filter the rotated tiles, larger tiles must initially be derived in order to avoid artifacts at the edges. The starting point hereby is a resultant tile with 32×32 image elements. Owing to the rotation of the tiles, it is necessary to take account of a greater number of image elements. This variable is given by double the root as the diagonal. The filtered tile of a size 32×32 must be derived through back-rotation of a tile having a minimum size to be buffered of 50×50 if a bilinear interpolation is undertaken during the rotation. Artifacts are completely avoided if this buffer is expanded to 52×52 image elements.
In order to obtain a valid area of a size 52×52 for filtration with a filter of 15×15 image elements, a tile to be buffered of a size 66×66 ultimately arises. FIG. 2 shows the individual sizes and rotations in undertaking the method in accordance with the invention, wherein it is assumed that, in order to filter a tile of 32×32 image elements, a tile of 46×46 image elements is talken from the image. A rotation of 45° then yields a tile of 66×66 image elements, of which, however, only an area of 52×52 image elements can be processed with a filter that is 15×15 image elements in size.
The broken line shows this area From this, however, results of the filtration can be exploited only if all the image elements covered by the particular filter position lie within the rotated 46×46 image-element tile. Following back-rotation, the filtered tile of a size 32×32 emerges, which must not overlap with other result tiles of the image.
FIG. 3 shows a black and white picture of a fingerprint image with a tile 1, as processed in the example shown in FIGS. 1 and 2.
FIG. 4 shows a Gabor filter formed in one direction by a Gaussian bell-shaped curve and in the other direction, which is at right angles to it, by a cosine oscillation modulated by a Gaussian bell-shaped curve.
Patent Application
20080031500
