Journal of Electrical Engineering and Automation

Pointer meters are widely used in key fields such as industry, electricity, and transportation. The accurate recognition of their readings is of great significance for system monitoring and fault early warning. Traditional manual reading methods are inefficient and error-prone, making it difficult to meet the needs of intelligent development. This paper focuses on the research of "application of deep learning in automatic reading recognition of pointer meters" and proposes an image processing method based on deep learning models, aiming to achieve high-precision and automated recognition of pointer meters in complex environments. By introducing convolutional neural networks and target detection technologies, the recognition capability under issues such as low pointer contrast and large angle changes is improved, verifying the feasibility and superiority of deep learning in this field.

Deep learning; Pointer meter; Automatic recognition; Image processing; Target detection