SSDA for Colored Target Based on Characteristic Differences

The paper proposes a sequential similarity detection algorithm (SSDA) for colored target based on characteristic differences. It analyzes basic SSDA, combines the characteristics of color, shape and size, then improves the SSDA. Experimental results show that the improved SSDA reduces the computational complexity, improves target identification accuracy, with better real-time.