Fingerprint Image Enhancement with Second Derivative Gaussian Filter and Directional Wavelet Transform
Keokanlaya Sihalath, Somsak Choomchuay, Shatoshi Wada, Kazuhiko Hamamoto · 2010
In this paper, we propose a technique for enhancing the quality of fingerprint images. Directional wavelet transform and second derivative of a Gaussian filter are applied. The original fingerprint image is decomposed into approximation and detail sub-images. To each sub-dimension a directional filter: second derivative of Gaussian filter is applied for tuning up the image features. The enhanced image is measured for its improvement by testing the success of core point identification where Poincare technique is used. The commonly-well-known database FVC-2004 is used in this study. The obtained results offer clean visualization as well as the increase the success of true core point detection.