改进的指纹图像自适应分割方法

Improved adaptive method for fingerprint image segmentation

指纹分割是指纹图像预处理中的重要一步。对传统的指纹分割算法分析比较,并且在基于灰度方差的指纹分割算法的基础上,利用指纹图像区域脊线和谷线间隔均匀出现的纹理特征提出一种自适应指纹图像分割算法,避免了凭经验确定阈值的问题。实验结果表明,相比于基于灰度方差的指纹图像分割算法,该算法的分割效果更好,对噪声的抵抗能力更强,且对不同类型的指纹图像有较高的适应性。

Fingerprint segmentation is an important step in the process of image preprocessing.The traditional fingerprint image segmentation algorithms are analyzed and compared,and a new adaptive fingerprint segmentation algorithm based on the variance based fingerprint segmentation algorithm is proposed.In the new algorithm,the texture feature which is represented by the uniform ridge and valley intervals is used to compute mean and threshold adaptively.The problem of determining threshold experientially is avoided.The experimental results show that the effect of segmentation of the proposed algorithm is better than the variance based fingerprint segmentation,and it also has stronger resistance to noise and higher adaptability to different types of fingerprint images.