改进的指纹细节特征提取算法

指纹细节特征（minutiae)提取是指纹自动识别的核心技术之一，常规的指纹细节特征提取算法需要先采用纹线跟踪的方法对细化后的指纹图象进行纹线修复，然后再实现细节特征提取，纹线修复不仅步骤繁琐，而且比较耗时，针对这一问题，提出了一种改进的指纹细节特征提取算法，该算法首先在细化后的指纹图象上直接提取原始细节特征点集，然后分析图象中存在的各类噪声及其特点，总结伪特征点的分布规律，最后，结合局部纹线方向信息，针对不同的噪声，采用针对性的算法，将各类噪声引起的伪特征点分别予以删除，最终保留下来的特征点集即视为真正的特征点集，为验证该算法的性能，将改进算法与常规算法进行了对比实验，实验结果表明，改进算法有效地减少了计算时间，细节特征提取准确率也基本可以满足应用的需要。

An Improved Algorithm for Minutiae Extraction in Fingerprint Images

Minutiae extraction is one of the core techniques of automatic fingerprint identification. Routine algorithm for minutiae extraction needs to restore ridges firstly by the way of ridge tracing on thinned fingerprint images and then minutiae extraction is realized. It is trivial and time consuming to restore ridge structure. Aiming at the problem, an improved algorithm for minutiae extraction is brought out. First, the set of original minutiae is directly extracted from thinned fingerprint images. Second, various noises in fingerprint images and their properties are analyzed and distributing regulation of pseudo minutiae is generalized. Last, combining with the information of local ridge direction, special algorithms are designed with respect to various noises to delete pseudo minutiae from original minutiae set. The remainders of original minutiae are viewed as intrinsic minutiae. To verify the performance of the improved algorithm brought out in this paper, contrastive experiment was conducted with routine algorithm. Experimental results indicate that computational time is reduced effectively with the improved algorithm and the accuracy of minutiae extraction can fill the demand of application.