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首页> 外文期刊>International Journal of Computer Science and Security >Adaptive and Faster Approach to Fingerprint Minutiae Extraction and Validation
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Adaptive and Faster Approach to Fingerprint Minutiae Extraction and Validation

机译:指纹特征提取和验证的自适应快速方法

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Fingerprint has remained a very vital index in the field of security where series of Automatic Fingerprint Identification System (AFIS) have been developed for human identification. Many of these systems involve matching each of the features of a template image with each of the features in the feature sets in the reference database to determine the level of match between the template and the reference images. Matching is done on the basis of preset parameters such as feature type, location, orientation and so on. Obtaining the features from the template image and for building a reference database involves the implementation of a sound fingerprint feature detection and extraction algorithm. In this paper, the process of detecting and extracting false and valid features contained in a fingerprint image is discussed. Some of the existing fingerprint features extraction algorithms were firstly modified and the resulting algorithms were implemented. The implementation was carried out in an environment characterized by Window Vista Home Basic as platform and Matrix Laboratory (MatLab) as frontend engine. Fingerprints images of different qualities obtained from the manual (ink and paper) and electronic (fingerprint scanner) methods were used to test the adequacy of the resulting algorithms. The results obtained show that only valid and true minutiae points were extracted from the images.
机译:指纹一直是安全领域中非常重要的指标,在​​那里开发了一系列自动指纹识别系统(AFIS)来进行人类识别。这些系统中的许多系统都涉及将模板图像的每个特征与参考数据库中特征集中的每个特征进行匹配,以确定模板和参考图像之间的匹配程度。匹配是根据预设参数(例如要素类型,位置,方向等)完成的。从模板图像获得特征并用于建立参考数据库涉及声音指纹特征检测和提取算法的实现。在本文中,讨论了检测和提取指纹图像中包含的虚假和有效特征的过程。首先修改了一些现有的指纹特征提取算法,并实现了所得算法。该实现是在以Window Vista Home Basic为平台和Matrix Lab(MatLab)为前端引擎的环境中进行的。从手动(墨水和纸张)和电子(指纹扫描仪)方法获得的不同质量的指纹图像用于测试所得算法的适当性。获得的结果表明,仅从图像中提取了有效和真实的细节点。

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