A Water-Level Measurement Method Using Sparse Representation

The water level measurement method based on image processing has entered a stage of rapid development in recent years due to its visibility and confirmability. However, the water level measurement method based on image processing is very susceptible to water stains, residual water level line, lighting conditions and other factors, and the measurement accuracy is difficult to compare with the traditional water level measurement method. This paper proposes a water level measurement method based on image processing and sparse representation. The experiment indicated that the method has a strong robustness to light variation, local disability, foreign matter occlusion, and so forth. Further, the maximum error of the method is less than 0.9 cm, which is significantly smaller than other image processing based water level recognition methods such as frame difference method, image segmentation method and Hough transform.