Enhanced Residual Orientation for Improving Fingerprint Quality

Fingerprint possesses unique, hard to lose, and reliable characteristics. In the recent years, it has been widely applied in biometrics. However, in fingerprint identification, blurred images often occur owing to uneven pressing force; and result in recognition errors. This study proposes an innovative fingerprint quality improvement algorithm to enhance the contrast of fingerprint image and to reduce blurs. By employing D4 discrete wavelet transformation, images are transformed from spatial domain to four frequency domain sub-bands. Then interactive compensation is performed on each band through the multi-resolution characteristic of wavelet transformation and singular value decomposition. Finally, compensated images are reconstructed through inverse-wavelet transformation. After going through our developed fuzzy fingerprint detection system, the fuzzy extent of compensated images can be effectively improved for later backend identification. This study employed NIST-4 and FVC fingerprint databases. The experimental results showed that our method actually could effectively improve blurs in fingerprint.