首先利用指纹方向一致性特征将指纹图像转换成具有较大灰度均匀区域的灰度图像。
First, we use coherence of orientation to turn fingerprint image into image with greater even gray areas.
指纹图像的预处理又可以分为灰度图滤波去噪、二值化、二值化图像去噪、细化和细化后去噪五个部分。
Fingerprint image pre-processing has five parts: filtration in gray-scale image, binarization, filtration in binary image, thinning and filtration in thinning image.
算法中通过合理的运用图像灰度特性，以较低的计算代价有效地解决了指纹图像分割问题。
This algorithm solves the problem of fingerprint image segmentation with low computational cost based on reasonable application of the gray-level-statistics of fingerprint images.
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