In this paper, we propose a fast and accurate scene recognition system from moving vehicle, which is a combination of Higher-order Local Auto-Correlation (HLAC) features and the linear discriminant analysis. The scene recognition system of moving vehicles should classify successive images into categories under limited computational resources, have robustness to cope with environmental changes, and adopt various scenes, which do not have explicit features. Our algorithm satisfies those requirements. We evaluated our algorithm in intersection and highway recognition experiments, and showed that our algorithm not only has comparable recognition accuracy compared with the state-of-the-art methods but also outperforms those methods in computational speed.
