Fingerprint Identification is one of the most reliable and popular personal identification methods. It can be divided into image acquisition, enhancement, feature extraction and matching steps. The enhancement stage is of great importance as it influences the performance of subsequent feature extraction and matching. In this paper, different image enhancement approaches presented in the scientific literature are reviewed. Many fingerprint enhancement algorithms were effective for medium or high quality fingerprint images. But these existing algorithms were either not suited for low quality fingerprint images, or too slow to satisfy the real-time requirements. We proposed a fingerprint enhancement algorithm based on Fourier filtering. In our algorithm the fingerprint enhancement were transformed from spatial domain to frequency domain by Fourier transforming. The fingerprints were enhanced by band-pass filter and directional filter in frequency domain. Experimental results show our algorithm is fast and has excellent enhancing performance for low quality fingerprints. In addition, Enhancement for non-minutiae based fingerprint recognition for low quality images is presented. the pre-processing stage operating on a hexagonal grid can be implemented efficiently and gives promising results. Methods of comparing the performance of enhancement methods are discussed. Conclusions are made regarding the importance of effective enhancement, especially for noisy or low quality images.
The fingerprint (FP) provides an optimal foundation for Automatic Personal Identification Systems. Over the last two decades significant progress in Automatic Fingerprint Identification Systems (AFIS) has been achieved. However, the performance of AFIS still suffers from the FP image quality captured by FP sensors, the enhancement techniques for FP images and feature extraction, and the available approaches of feature matching. In this paper, we proposed a fingerprint enhancement algorithm based on Fourier filtering. In our algorithm the fingerprint enhancement were transformed from spatial domain to frequency domain by Fourier transforming. In addition, Fingerprint matching is one of the most important problems in AFIS. We proposed a minutia matching algorithm. In our algorithm, a simpler alignment method is used. We introduced ridge information into the minutia matching process in a simple but effective way and solved the problem of the matching of vector pairs with low computational cost.
The fingerprint (FP) provides an optimal foundation for Automatic Personal Identification Systems. In this paper, A new method of fingerprint collection that based on the improvability of images quality is proposed. The approach is mainly to enhance the accuracy of Automatic Fingerprint Identification Systems (AFIS) by indirect-contact collection. In a preliminary stage, The capture of fingerprint images is tested with an available contact approaches. Similarly captured clear images by using semiconductor capacitive sensor. And then, The integrited nondistortion fingerprint is indirect-contact collected by using a super-hemisphere-immerge lens and CCD camera with laser or incoherent light. It compares both of two collect methods on the basis of the experiments. The methods of fingerprint optical correlate identification and pattern recognition are discussed. The methods simply achieves on system.
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