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中文摘要：
研究了一种基于曲波域的指纹图像预处理方法。首先将指纹图像在曲波域中分解,然后用Gabor滤波器来处理粗尺度系数,这些系数是原图像的近似值;同时,在细尺度系数上使用软阈值函数减少沿着脊线方向的噪声。再将重构以后的图像二值化,最后使用基于模板的脉冲耦合神经网络（PCNNs）细化算法细化二值图像,得到指纹的骨架图像。实验结果表明,该方法优于传统的基于Gabor滤波器的指纹图像预处理方法。
英文摘要：
A method based on curvelet domain for pre-processing the fingerprint images is proposed.First,the fingerprint image should be decomposed in curvelet domain,than we use Gabor filters on coarse scale coefficients which values are the original image approximation;meanwhile,we use a soft threshold on fine scale coefficients to decrease the effect of noise along the ridge directions.Then,after binarizing the reconstructed fingerprint image,we use a image thinning method based on template-based pulse-coupled neural networks（PCNNs） to thin the binary image,and get the skeleton image.The simulation results show that the proposed fingerprint pre-process method is better than the traditional method which is based on Garbor filters.
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