Ear Pattern Based Person Recognition
J. Vijaya, Abhay Tiwari, Shubham Raj, Zorawar Singh · 2023
The use of ear images for automatic identification is an intriguing area of research in the field of biometrics. Similar to other identifying biometrics such as the visage, iris, and fingerprint, the ears contain numerous distinguishing characteristics. As many individuals wear masks, the majority of the scientific community is aware of the negative aspects of the current COVID-19 outbreak. The human ear is the finest material for accurate diagnosis because it does not require the participation of the individual we are attempting to detect, and its structure has not changed significantly over time. Even with a mask, the ear is visible, so locating it is simple. In the human body identification process, ear bio-metrics can be added to other biometric systems to provide identification signals when information from other systems cannot be trusted or is unavailable. This paper describes a deep convolutional neural network architecture with six layers for auditory recognition. The biometrics field has a novel tool for recognizing ear patterns. It is used extensively in image processing, pattern recognition, etc., and has a high theoretical research value and commercial application potential. This project employs the most advanced techniques presently in use to recognize the same people's ear patterns in order to address the problem of inconsistency and to explore the human ear pattern quickly. - Bio-metric modules designed in accordance with industry standards. Utilizing the AMI Ear dataset, evaluate the efficacy of the proposed system in a controlled environment. This method can be used in conjunction with qualitative analysis to identify unique individuals within a large population.