Real-Time Model-Based Hand Localization for Unsupervised Palmar Image Acquisition

摘要

Unsupervised and touchless image acquisition are two problems that have recently emerged in biometric systems based on hand features. We have developed a real-time model-based hand localization system for palmar image acquisition and ROI extraction. The system operates on video sequences and produces a set of palmprint regions of interest (ROIs) for each sequence. Hand candidates are first located using Viola-Jones approach and then the best candidate is selected using model-fitting approach. Experimental results demonstrate the feasibility of the system for unsupervised palmar image acquisition in terms of speed and localization accuracy.