GEHE: A multifactored model of soft and hard biometric trait for ease of retrieval

Biometric systems are broadly classified into unimodal and multimodal system. Attempt to ameliorate the inadequacies of the unimodal systems brought about the use of multimodal systems. Multimodal comprises of both the hard (capable of unique identification) and soft (not necessarily unique) biometric traits. Employing this provision for enrolment, identification and verification usually result into increased time complexity during search for desired template. It is a common understanding that soft biometric traits cannot uniquely identify an individual however it can be used to complement the rate of identification. A critical issue in multimodal systems is the resultant large database to store multiple traits at the enrolment phase and the amount of time it takes to search through the database during identification. This paper employs a fusion model alongside ordered pairs of soft biometric traits (Gender, Ethnicity, Hair color, Eye color - GEHE) to cluster n-dataset of two primary biometric features (face and fingerprints) towards enhancing the retrieval time and subsequent identification of target template.