| 摘要 |
Disclosed is a recognition system adopting visual observation confidence (VOC) for a robust face recognition system, for example, GMM, HMM, etc., using sub-block-based features. A flatness measure, a centrality measure, and an illumination measure are suggested as measures of the VOC and the suggested measures are combined into a single VOC by linear combination. When physical weighted summation is conducted, weight values are determined according to contribution factors of each confidence. The flatness measure not only creates attributes withstanding illumination but also reduces the influence of less discriminative blocks. The centrality measure maintains the influence of important components such as eyes, a nose, a mouth, etc., while reducing the influence of hair, a neck, and background blocks which are less contributive to face recognition. The illumination measure reduces the influence on a recognizer by detecting shadows and highlighted areas from an intra-variance function of average brightness (Lu) of each block. The present invention is provided from a different perspective from existing methods, for example, feature extraction resistant to illumination, a face image enhancement technique, and multi-modal recognition, and has the novelty thereof in that the contribution factors are calculated and applied to recognition of each image block. |
