Multimodal biometric system built on the new entropy function for feature extraction and the Refined Scores as a classifier. Issue 7 (1st May 2015)

• Record Type: Journal Article
• Authors: Mamta; Hanmandlu, Madasu
• Is Part Of: Expert systems with applications. Volume 42:Issue 7(2015)
• Page Start: 3702
• Page End: 3723
• Publication Date: 2015-05-01
• Subjects: Expert systems (Computer science) -- Periodicals; Systèmes experts (Informatique) -- Périodiques; Electronic journals; 006.33
• DOI: 10.1016/j.eswa.2014.11.054
• Languages: English
• ISSNs: 0957-4174

Abstract

<abstract xml:lang="en" abstract-type="author-highlights" id="ab005"> <title id="st310">Highlights</title> <sec> <p id="sp0005"> <list id="l0005"> <list-item id="o0005"> <label></label> <p id="p0460">A new entropy that can modify the probabilities in the function is formulated.</p> </list-item> <list-item id="o0010"> <label></label> <p id="p0465">Two information set based features: EGI and EEI are derived from the above function.</p> </list-item> <list-item id="o0015"> <label></label> <p id="p0470">A unique multimodal biometric system comprising IR face, iris and ear is developed.</p> </list-item> <list-item id="o0020"> <label></label> <p id="p0475">A classifier based on Refined Scores that use cohort scores in refining is devised.</p> </list-item> <list-item id="o0025"> <label></label> <p id="p0480">The combined scores from individual modalities are fused at the score level fusion and then improved by RS method.</p> </list-item> </list> </p> </sec> </abstract>