适应于户外场景下低成像质量的指针式表计读数智能识别方法OA北大核心CSTPCD

Due to the influence of lighting conditions on image acquisition by intelligent inspection meter devices in outdoor settings,the quality of captured images is often low,making it difficult to accurately read the meter.To address this issue,this paper introduces a method for outdoor inspection meter reading.The method comprises dial detection and reading detection components.After dials are efficiently detected by using a trained feature detection model,the detected candidate box images undergo preprocessing and binary image reconstruction based on contour detection.Subsequently,the scale line detection and pointer detection are performed in the reconstructed binary image,followed by obtaining me-ter readings using an angular method.Experimental verification demonstrates that the proposed method mitigates the effects of image blurring,glare,sunlight shadows,and other factors affect the image quality in outdoor scenarios.The av-erage false detection rate and average miss detection rate for dial targets under five common lighting conditions are 1.005%and 0.505%,respectively.The average time for single image detection is 28.1 ms with a reading detection accu-racy of 93.91%.This method proves to be applicable and effective for accurate reading of pointer-type meters at substations under complex lighting conditions.