This paper presents camera-based road surface marking detection methods suited to sensor fusion-based positioning system that consists of low-cost GPS (Global Positioning System), INS (Inertial Navigation System), EDM (Extended Digital Map), and vision system. The proposed vision system consists of two parts: lane marking detection and road surface marking detection. The lane marking detection provides regions that are highly likely to contain road surface marking. The road surface marking detection detects road surface markings in ROI (Region of Interest) established between the lane markings, and classifies their types. In order to ensure real time operation, the proposed system varies the gating for lane marking detection and changes detection methods according to the FSM (Finite State Machine) about the driving situation. Further, a single template matching is used to extract features for both lane marking detection and road surface marking detection, and it is efficiently implemented by horizontal integral image.