基于主成分分析和边缘检测的指纹访问控制
A Fingerprint-based Access Control using Principal Component Analysis and Edge Detection
摘要：
本文提出了一种新的方法来决定是否适当的采集到的指纹图像到一个给定的数据库。该过程开始于通过结合主成分分析（PCA）和边缘检测构建的图像空间中的训练基的组装。然后，参数H，一个新的功能，有助于在数据库中的指纹图像的相关性的决策，来自欧几里德和马氏距离之间的关系。该过程以提升受试者操作特征（ROC）的曲线结束，其中根据假阳性和假阴性的可接受率选择在参数H上定义的阈值。
英文摘要：
This paper presents a novel approach for deciding on the appropriateness or not of an acquired fingerprint image into a given database. The process begins with the assembly of a training base in an image space constructed by combining Principal Component Analysis (PCA) and edge detection. Then, the parameter H, a new feature that helps in the decision making about the relevance of a fingerprint image in databases, is derived from a relationship between Euclidean and Mahalanobian distances. This procedure ends with the lifting of the curve of the Receiver Operating Characteristic (ROC), where the thresholds defined on the parameter H are chosen according to the acceptable rates of false positives and false negatives.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
