Application of Image Processing Technology in the Identification of Sediment Dosing and Flocculation Process

Aiming at the composition and nature of river and lake mud in space and time have greater complexity and uncertainty, there are dosing treatment of intelligent difficulties and other issues, this paper uses image processing technology to identify the mud flocculent, image edge detection and image segmentation technology as the image processing method, respectively, to extract the flocculent group contour and the size of the area and other parameter information, to explore the advantages and applicability of different image processing methods in the process of river and lake mud dosing and identification of flocculent groups. To investigate the advantages and applicability of different image processing methods in the identification process of flocculating groups in river and lake mud dosing, to provide a basis for the realization of intelligent processing of bottom mud dosing, and to improve the efficiency and effect of dewatering treatment, the results show that the edge detection methods based on Canny, Sobel and Laplacian are ineffective in the process of flocculating images of bottom mud dosing in river and lake mud, and the maximal Precision, Recall and F1 are 0.38, 0.57, 0.4 and 0.4, respectively., 0.57, and 0.4, and the threshold-based image segmentation method has better applicability, with its Precision, Recall, and F1 reaching 0.88, 1.00, and 0.94, respectively.