Data fusion and information quality for biometric identification from multimodal signals [Modelo jdl y calidad de la información para identificación biométrica a partir de señales multimodales: Estudio exploratorio] (2020)
Biometric identification is carried out by processing physiological traits and signals. Biometrics systems are an open field of research and development, since they are permanently susceptible to attacks demanding permanent development to maintain their confidence. The main objective of this study is to analyze the effects of the quality of information on biometric identification and consider it in access control systems. This paper proposes a data fusion model for the development of biometrics systems considering the assessment of information quality. This proposal is based on the JDL (Joint Directors of Laboratories) data fusion model, which includes raw data processing, pattern detection, situation assessment and risk or impact. The results demonstrated the functionality of the proposed model and its potential compared to other traditional identification models. © 2020, Associacao Iberica de Sistemas e Tecnologias de Informacao. All rights reserved.