xmlui.ArtifactBrowser.SimpleSearch.filter.source:Proceedings of 34th International Business Information Management Association Conference. Vision 2025: Education Excellence and Management of Innovations through Sustainable Economic Competitive Advantage, IBIMA 2019
xmlui.ArtifactBrowser.SimpleSearch.filter.event34th International Business Information Management Association Conference. Vision 2025: Education Excellence and Management of Innovations through Sustainable Economic Competitive Advantage, IBIMA 2019 (13.11.2019 - 14.11.2019, Madrid)
Abstract:
Biometric systems are often discussed today. Authentication systems that work with biometric data (such as fingerprint, iris, hand geometry) have a high level of security. There are many reasons why it is necessary to have a strong authentication system. One of them is the existence of information systems that store sensitive data that needs to be protected. This article is focused on hand-based identification systems. A typical hand-based authentication system performs: data acquisition, feature extraction, classification, and decision. This paper presents the use of a convolutional neural network to identify people based on hand geometry. Convolutional neural networks are used for pattern recognition. When using a convolutional neural network, it is not necessary before classification feature extraction. Experiments were performed on a database of 550 hand images from 114 people, each person provided 5 images. The accuracy of the identification of persons was 94.11%, 3 images of each person were used for training.
