Fingerprint segmentation based on local Fourier transform

The segmentation of fingerprint images plays an important role in fingerprint recognition. A new algorithm based on Local Fourier Transform (LFT) for the fingerprint segmentation is proposed in this paper. Firstly, we perform the Local Fourier Transform on image to get eight independent Local Fourier coefficients per pixel. Then, block features are extracted by calculating the 2(nd), 4(th), 6(th) order moments of the local Fourier coefficients of every pixel in the block. After that, a Fisher linear discriminant classifier is trained for the classification per block. Finally, mathematical morphology and region boundary smoothing is applied as postprocessing to obtain compact clusters and to reduce the number of classification errors. The experimental results on the databases of FVC2004 demonstrate the robustness and the efficiency of the proposed method.