| Traditional mechanical water meters are still dominant in the market due to their low prices,accurate metering,mature technology,and stable supply and sales channels.Although smart water meters are gradually emerging,replacing traditional mechanical water meters must invest a lot of manpower,material and financial resources,purchase new equipment,and build corresponding water systems.The transformation process will certainly be very slow.With the advent of the era of intelligence,people’s demand for intelligence is getting higher and higher,but water companies still use the traditional manual meter reading method,which is inefficient and cumbersome,and users will be dissatisfied due to inevitable manual misoperation,thus affecting the corporate image.In this case,it is particularly important to design an automatic meter reading identification system,which can not only reduce the labor cost of the enterprise,but also greatly improve the work efficiency and accuracy.The process of water meter digital recognition can be divided into three stages:digital area positioning,character segmentation and character recognition.In the stage of digital area positioning,previous studies were mostly based on strict prerequisites,which limited the style of water meters,and had strict requirements on lighting conditions,shooting environment,shooting distance,etc.However,in actual life use,due to the different production batches,locations,photographing times,and dial contamination of water meters,ignoring the above factors will have a great impact on actual production and use,and the developed system will not Has better robustness.In order to be able to accurately locate the digital area of the water meter under the above various uncertainties,inspired by the idea of text detection,this paper proposes a network model based on the text detection algorithm DBNet,and uses data enhancement technology to achieve digital area localization.The experimental results verify the effectiveness of the algorithm,and it has achieved good positioning results for different styles of water meters and under various complex environmental factors.In the process of digital recognition,the quality of character segmentation directly affects the accuracy of the recognition results.In the character segmentation stage,in view of the problem of uneven illumination in the digital area,this paper finally chooses to use the local binarization algorithm to obtain binary images through experimental comparison,and then proposes a character segmentation method based on morphology,connected areas and mapping.Character segmentation in digital areas.The experimental results show that this method has achieved good segmentation results for digital areas with uneven illumination and dial pollution.In the final character recognition stage,this paper uses the template matching method for digit recognition.Aiming at the slight difference in character interval caused by different water meter styles,different production batches,and incorrect recognition caused by the use of the same fixed template,this paper further improves the matching template based on previous research.The improved template also solves the problem in previous research.For the problem of matching whole characters and half-characters separately,you only need to splicing the half-characters to form a new to-be-matched character to use this template for matching.Finally,in order to solve the problem that the size of the new characters formed by half-character splicing is inconsistent with the whole character,which leads to the decrease of matching accuracy,a multi-scale template matching method is proposed in this paper.The experimental verification shows that this method can effectively recognize numbers,not only with high efficiency but also with high accuracy. |
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