Synthesizing multilevel abstraction ear sketches for enhanced biometric recognition

David Freire-Obregón, João Neves, Ziga Emersic, Blaz Meden, Modesto Castrillón Santana, Hugo Proença

Abstract: Highlights•Sketch-Based Datasets Expansion: Leveraging CLIPasso, we transformed ear images into sketches at various abstraction levels, preserving key features and introducing a novel data representation for biometric analysis.•Triplet-Loss Function Enhancement: Adapting the triplet-loss function to incorporate multiple abstraction levels significantly improves recognition performance over traditional methods.•Comparative Backbone Analysis: An exhaustive evaluation of different backbones highlights their effectiveness in sketch-based ear recognition, guiding advancements in biometric technologies.•Cross-Dataset Generalizability Tests: Training on combined datasets and testing on distinct ones validate our approach’s robustness and effectiveness against unseen data distributions.