Multispectral Texture Features from Visible and Near-Infrared Synthetic Face Images for Face Recognition
Recently, high-performance face recognition has attracted research attention in real-world scenarios. Thanks to the advances in sensor technology, face recognition system equipped with multiple sensors has been widely researched. Among them, face recognition system with near-infrared imagery has been one important research topic. In this paper, complementary effect resided in face images captured by nearinfrared and visible rays is exploited by combining two distinct spectral images (i.e., face images captured by near-infrared and visible rays). We propose a new texture feature (i.e., multispectral texture feature) extraction method with synthesized face images to achieve high-performance face recognition with illumination-invariant property. The experimental results show that the proposed method enhances the discriminative power of features thanks the complementary effect.