Abstract
This paper proposes a novel method to detect the water level of a river or reservoir. Images of the ruler which is used to measure the water level are obtained easily from a camera installed on the bank. Based on the property of the images captured by the camera, the problem of water level calculation can be transformed to the problem of classifying each image into two classes of ruler and water. As dictionary learning model has shown, its ability and efficiency in image classification problems, it is utilized in this paper to solve the problem of water level detection.
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References
Sulistyowati R, Agus Sujono H, Khamdi Musthofa A. Design and field test equipment of river water level detection based on ultrasonic sensor and SMS gateway as flood early warning. In: AIP conference proceedings, vol. 1855; 2017. p. 50003.
T. Mantoro T, Istiono W. Saving water with water level detection in a smart home bathtub using ultrasonic sensor and Fuzzy logic. In: 2017 second international conference on informatics and computing (ICIC); 2017. p. 1–5.
Breuer E, Heitsenrether R, Fiorentino L, Hensley W, Krug W. Error analysis of water level measured from a bottom mounted ocean platform. In: OCEANS 2017—Anchorage; 2017. p. 1–8.
Loizou K, Koutroulis E, Zalikas D, Liontas G. A low-cost capacitive sensor for water level monitoring in large-scale storage tanks. In: 2015 IEEE international conference on industrial technology (ICIT); 2015. p. 1416–21.
Poovizhi S, Premalatha M, Nivetha C. Automatic water level monitoring and seat availability details in train using wireless sensor network. In: 2017 international conference on computation of power, energy information and communication (ICCPEIC); 2017. p. 321–4.
Kim K, Lee N-K, Han Y, Hahn H. Remote detection and monitoring of a water level using narrow band channel. J. Inf. Sci. Eng. 2010;26:71–82.
Skretting K, Husøy J. Texture classification using sparse frame-based representations. EURASIP J Adv Sig Process. 2006;2006(1):52561.
Wang X, Gu Y. Cross-label suppression: a discriminative and fast dictionary learning with group regularization. IEEE Trans Image Process. 2017;26(8):3859–73.
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Pan, J., Fan, Y., Dong, H., Fan, S., Xiong, J., Gui, G. (2020). Image-Based Detecting the Level of Water Using Dictionary Learning. In: Liang, Q., Liu, X., Na, Z., Wang, W., Mu, J., Zhang, B. (eds) Communications, Signal Processing, and Systems. CSPS 2018. Lecture Notes in Electrical Engineering, vol 516. Springer, Singapore. https://doi.org/10.1007/978-981-13-6504-1_3
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DOI: https://doi.org/10.1007/978-981-13-6504-1_3
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