Method on water level ruler reading recognition based on image processing

Water level measure is the key task in hydrological monitoring, wherein water level ruler (WLR) is the necessary enabled measure instrument. Due to its low cost and easy deployment, WLR has been widely used for flood monitoring in many hydrological stations. For saving labor costs, it is very desirable to achieve automatic reading of WLR, which has recently become a focus of the research in hydrological field. However, in automatic reading of WLR, there exist several issues or challenges, which mainly include low recognition rate of characters on WLR and low precision in calculating water level. To address these issues, in this paper we propose a practical and efficient method which is based on image processing. The proposed method consists of three important components, i.e., (1) a multi-template matching algorithm to recognize the characters on WLR, (2) a sequence verification algorithm to check and refine the recognized characters, and (3) a projection height comparison method to achieve accurate reading even under the circumstance of incomplete characters. We conduct experiments on real-world data to verify the efficiency of our proposed method. The experiment results show that the proposed method achieves $$63\%$$ recognition rate of characters on WLR, as well as average measure error of $$\pm {0.90\hbox { cm}}$$ which is much smaller than the national error standards on water-level monitoring in China ($$\pm {1.0\hbox { cm}}$$). Therefore, we believe our proposed method could be useful for facilitating effective water level measure in practice.