Multi-Template Processing of Fingerprint Recognition Algorithm

Using multi-template processing algorithm, the fingerprint features are accurately collected. Through normalization, make the black and white point contrast of the fingerprint image more obviously, strengthen the ridge line texture. Direction calculating algorithm is based on the grey value of the neighborhood pixels. It can be implemented simply and speedily. Through direction filter, noises can be removed, and the contrast of the fingerprint’s ridge lines and valley lines can be enhanced. After binary converting, all information of the fingerprint is stored with 0 and 1. The effect of thinning is to make the fingerprint image more distinct to extract the fingerprint feature point easily. These steps had been implemented on Altera DE2 board with HDL codes. The experimental results indicate that the multi-template algorithm of fingerprint image processing is correct and practicable.

The Development of Wavelet Transform and its Application in Image Denoise

The paper introduces Laplace pyramid, Ridgelet and Curvelet principle, structure and methods, and their denoising experimental studies. It also introduces the traditional direction filter of principle, structure and methodology, and the simulation experiments show that its image denoising PSNR is slightly lower than wavelet but denoising image visual quality is better than former. To that end, proposed a new direction filters that uniform direction filter banks and non-uniform direction filters, proved filter passband condition and related design and implementation issues were discussed. nonlinear experiment shows that the new direction filter bank was better than the wavelet.