Ear Recognition

Ear recognition, a biometric modality focusing on the unique characteristics of the human ear, is gaining traction for its potential in identification and authentication systems. Current research emphasizes improving accuracy and robustness using deep learning techniques, particularly convolutional neural networks (CNNs) like VGG16, MobileNet, and Mask-RCNN, often incorporating data augmentation and transfer learning strategies. This field is significant for its potential applications in security, healthcare (e.g., diagnosing ear diseases), and virtual reality (improving audio rendering), driving the development of large-scale datasets and novel algorithms for ear detection, segmentation, and recognition across diverse populations and conditions.