The present invention relates to the field of
power tool detection, and more specifically, to a
power tool detection method based on
machine vision. The method comprises: continuously acquiring multiple frames of surface
grayscale images of power lines, performing mixed
Gaussian statistics on the surface
grayscale images to obtain a pixel value distribution curve, calculating a
clarity index according to the pixel value distribution curve, and retaining surface
grayscale images with a
clarity greater than a preset
clarity threshold; calculating the
overlap coefficient between a target image and a
reference image, traversing to obtain the
overlap coefficient between the target image and the
reference image at different positions, and in response to the maximum
overlap coefficient, obtaining the relative position of the target image and the
reference image, traversing to obtain the relative position of any two adjacent frames of surface grayscale images; splicing the surface grayscale images according to the relative position to obtain a power line map, inputting the power line map into a preset neural network, outputting a defect probability value, and completing the detection. Through the technical solution of the present invention, the accuracy and efficiency of the
power tool detection results can be improved.