一种新的指纹图像合成分割法

在研究和分析传统方差法和最大类间方差法的基础上,提出了一种传统方差法和最大类间方差法相结合的分块处理分割算法。该算法首先求出整个指纹图像的方差,然后计算每一子块的方差。若方差小于整个图像的方差则用方差法对图像进行分割,否则用最大类间方差法进行分割。最后再对图像进行平滑处理。实验结果表明,相对于传统分割方法,该方法无需根据经验选取阈值,能较准确地分割出前景和背景,抗噪能力强,对高对比度和低对比度的图像均具有很好的分割效果。

A new compound segmenting method on fingerprint image

After investigating and analyzing the traditional variance method and the maximum between-cluster variance, this paper presents a new approach to segment the fingerprint images based on the maximum between-cluster variance and sub-block processing of the traditional variance segmenting. The method firstly calculates the variance of the fingerprint image and each subblock. Traditional variance is used to segment the image if the variance of each sub-block is less than the variance of the entire image. Otherwise, the OTSU method is used and finally smooth the fingerprint image. The experimental results indicate that this method does not need to choose the threshold with the experience compared with the traditional methods, and the can accurately separate the prospects from context. This method performs well on both of the fingerprint images with high and low contrast. The segment algorithm not only provides good segment result but also is robust to reduce noise.