Fingerprint matching using ridge feature maps

1. A method for matching fingerprint images, the method comprising the steps of:

acquiring a query image of a fingerprint;

extracting a minutiae set from the query image;

comparing the minutiae set of the query image with a minutiae set of at least one template image to determine transformation parameters to align the query image to the at least one template image and to determine a minutiae matching score;

filtering the query image with a plurality of filters, wherein a filtered query image results from each of the plurality of filters;

square tessellating each of the filtered query images into a plurality of cells;

measuring a variance of pixel intensities in each of the plurality of cells to determine a feature vector for each filtered query image;

combining the feature vectors of each of the filtered query images wherein a ridge feature map of the query image is constructed;

comparing the ridge feature map of the query image to a ridge feature map of the at least one template image to determine a ridge feature matching score; and

combining the minutiae matching score with the ridge feature matching score resulting in an overall score, the overall score being compared to a threshold to determine if the query image and the at least one template image match.

2. The method as in claim 1 , further comprising the step of enhancing the acquired query image.

3. The method as in claim 1 , further comprising the step of segmenting foreground information from background information of the acquired query image.

4. The method as in claim 1 , wherein the plurality of filters are tuned to a frequency corresponding to an average inter-ridge spacing in the query image.

5. The method as in claim 1 , wherein a size of each of the plurality of cells is determined to be about a width of two ridges of the fingerprint image.

6. The method as in claim 1 , wherein the comparing the minutiae sets step comprises the step of generating a correspondence map pairing minutiae points from the query set and the at least one template set.

7. The method as in claim 1 , wherein the ridge feature matching score is a sum of feature vector distances in corresponding tessellated cells.

8. The method as in claim 1 , wherein the plurality of filters are rotated by the transformation parameters.

9. The method as in claim 1 , wherein the at least one template image includes a plurality of template images and an overall matching score is determined for each of the plurality of template images.

10. The method as in claim 9 , further comprising the step of determining a template image with the highest overall matching score, the highest matching score template image being a closest match to the query image.

11. A computer readable medium storing a computer program of instructions, executable by a computer to perform method steps for matching fingerprint images, the method comprising the steps of:

acquiring a query image of a fingerprint;

extracting a minutiae set from the query image;

comparing the minutiae set of the query image with a minutiae set of at least one template image to determine transformation parameters to align the query image to the at least one template image and to determine a minutiae matching score;

filtering the query image with a plurality of filters, wherein a filtered query image results from each of the plurality of filters;

square tessellating each of the filtered query images into a plurality of cells;

measuring a variance of pixel intensities in each of the plurality of cells to determine a feature vector for each filtered query image;

combining the feature vectors of each of the filtered query images wherein a ridge feature map of the query image is constructed;

comparing the ridge feature map of the query image to a ridge feature map of the at least one template image to determine a ridge feature matching score; and

combining the minutiae matching score with the ridge feature matching score resulting in an overall score, the overall score being compared to a threshold to determine if the query image and the at least one template image match.

12. The computer readable medium as in claim 11 , wherein the plurality of filters are tuned to a frequency corresponding to an average inter-ridge spacing in the query image.

13. The computer readable medium as in claim 11 , wherein a size of each of the plurality of cells is determined to be about a width of two ridges of the fingerprint image.

14. The computer readable medium as in claim 11 , wherein the comparing the minutiae sets step comprises the step of generating a correspondence map pairing minutiae points from the query set and the at least one template set.

15. The computer readable medium as in claim 11 , wherein the ridge feature matching score is a sum of feature vector distances in corresponding tessellated cells.

16. The computer readable medium as in claim 11 , wherein the plurality of filters are rotated by the transformation parameters.