Fingerprint Image De-Noising Using Wavelet Transform with the Comparison of Filtered and After Compression Filtered Noise Image

摘要

Fingerprint is becoming the part of our day to day life right from our home to workplace. Now a days for security and safety purpose prime importance is given by it. Also, Fingerprint identification is one of the most popular biometric technologies and which is highly used in criminalinvestigations, commercial applications, and so on. The performance of a fingerprint image-matching algorithm depends heavily on the quality of the input fingerprint images. It is very important to acquire good quality images. The use of wavelet transform improves the quality of an image andreduces noise level. So, in this research, different compression techniques are used to overcome this problem. Also, we have used different wavelets transformation for compression of fingerprint images. Image quality before compression and after compression are measured by Mean Squared Error(MSE), Signal-to-Noise Ratio (SNR) and Peak Signal-to-Noise Ratio (PSNR). This work is done in MATLAB using DSP and wavelet toolbox. At last, we have compared the filtered noise image method and the compression filtered noise image method.