Research on Accurate Measurement of Dynamic Coal Gangue Size Through Coordinate-Pixel Calibration Combined with Canny Edge Detection

Accurate measurement of dynamic coal gangue size directly affects the grasping strategy of the coal gangue sorting robot, but there is still a lack of fast and effective measurement methods. To target this problem, a dynamic coal gangue size measurement method combining image coordinate-pixel calibration and Canny edge detection is proposed. Firstly, a dynamic coal gangue image acquisition system is built, and the actual size of the coal gangue is obtained by three-dimensional scanning reconstruction as a comparison benchmark. Then, through image coordinate measurement, pixel benchmark setting, and coordinate-actual size conversion model construction, combined with gray-scale conversion, Gaussian filtering, and Canny edge detection instead of traditional binarization processing, the accurate extraction of coal gangue image contour is realized. On this basis, non-maximum suppression, double threshold lag selection and morphological operation are introduced to optimize the edge detection effect, and the shadow removal technology is combined to further improve the measurement accuracy. Finally, dynamic measurement experiments are carried out under seven different working conditions to compare the measurement accuracy and stability before and after optimization. The results show that the average measurement accuracy of the optimized method is more than 98%, the measurement error is less than 1.2 mm, and the single frame processing time is about 6 ms, which meets the real-time sorting requirements. This research provides an effective technical scheme for the size measurement of dynamic irregular objects.