학술논문

Ear Detection Based on Arc-Masking Extraction and AdaBoost Polling Verification
Document Type
Conference
Source
2009 Fifth International Conference on Intelligent Information Hiding and Multimedia Signal Processing Intelligent Information Hiding and Multimedia Signal Processing, 2009. IIH-MSP '09. Fifth International Conference on. :669-672 Sep, 2009
Subject
Communication, Networking and Broadcast Technologies
Computing and Processing
Signal Processing and Analysis
Ear
Detection algorithms
Face detection
Face recognition
Image edge detection
Skin
Head
Fingerprint recognition
Biometrics
Principal component analysis
ear detection
AdaBoost
Language
Abstract
This paper proposes a simple but practical 2D ear detection algorithm based on arc-masking candidate extraction and AdaBoost polling verification. In the first half phase of the proposed ear detection algorithm, a few ear candidates are extracted by arc-masking edge search followed by multilayer mosaic and orthogonal projection histogram. Then, in the second half phase, the most likely ear candidate is picked out by rough AdaBoost polling verification. Experimental results show that the proposed ear detection algorithm can achieve a bit higher detection hit rate and much lower detection false alarm rate than conventional AdaBoost ear detection algorithm with Haar-like features under various pose rotation conditions.