Human ear is an intriguing individual anatomical part of a passive, physiological biometrics systems based on the image acquired from digital cameras. The human ear has many singular features that permit the finding of particular individuals. It could be implemented as effective biometrics systems, for example, in crowd surveillance and identifying terrorist at public places such as airports, as well as controlling access to government offices.
Challenges and issues faced in the field of human identification using ear detection and recognition includes problem of occlusion, varieties in illumination, and real-time implementation in accessing information from an integrated database system with higher accuracy. Research on ear detection and recognition systems have been developing in a steady rate and mostly are constrained to controlled indoor environment. Notwithstanding, other research issues incorporate; ear print criminology; ear symmetry; and ear uniqueness.
This paper presents a review of existing biometric system based on ear features and proposes a novel hybrid ear recognition framework for the advancement of passive human identification technology. The aim of this work is to build a passive identification system for hybrid ear biometric from digital image database that is collected from two types of identifiers (right-left ear of the same person).
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To Cite this Article: Alemran, A., & Rahmatullah, B. (2019). Novel Hybrid Ear Recognition Framework in Passive Human Identification. International Journal of Academic Research in Business and Social Sciences, 9(14), 63–70.
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