publication . Article . 2016

Discriminant Correlation Analysis: Real-Time Feature Level Fusion for Multimodal Biometric Recognition

Mohammad Haghighat; Mohamed Abdel-Mottaleb; Wadee Alhalabi;
Open Access
  • Published: 17 May 2016
Abstract
Information fusion is a key step in multimodal biometric systems. The fusion of information can occur at different levels of a recognition system, i.e., at the feature level, matching-score level, or decision level. However, feature level fusion is believed to be more effective owing to the fact that a feature set contains richer information about the input biometric data than the matching score or the output decision of a classifier. The goal of feature fusion for recognition is to combine relevant information from two or more feature vectors into a single one with more discriminative power than any of the input feature vectors. In pattern recognition problems,...
Persistent Identifiers
Subjects
free text keywords: Biometrics, Feature (machine learning), Dimensionality reduction, Computer science, Feature (computer vision), Pattern recognition, Kanade–Lucas–Tomasi feature tracker, k-nearest neighbors algorithm, Feature extraction, Feature vector, Artificial intelligence, business.industry, business
Any information missing or wrong?Report an Issue