Abstract: In view of problems of high failure rate and easy to be affected by incline of shearer in the application of contact-type monitoring method of hydraulic support in environment of mine fog and dust, a monitoring method of recovery stae of hydraulic support guard plate based on image recognition was proposed. The method uses fog dust image sharpening algorithm and machine vision measurement method to carry out monitoring of recovery angle of the guard plate of the hydraulic support, and determines the recovery state of the guard plate of the hydraulic support by measuring the angle of the guard plate. Firstly, an improved dark channel prior algorithm and a multi-scale Retinex algorithm with guided filtering are adopted to defog the captured image, and then wavelet fusion is carried out on the defogging image, focusing on restoring the edge details of the image of fog and dust. Then, the region of interest (ROI) of the fusion image is extracted, binarized and processed by horizontal and vertical projection with machine vision measurement method, the skeleton and skeleton pixel points are extracted and generated into straight lines by fitting, coordinate transformation is carried out by the calibrated CCD camera to output true angle of the guard plate, so as to judge whether the guard plate is recovered. The experimental results show that the method realizes sharpening process of images with fog and dust in underground coal mine, and keep the detail of the image, and has accurate measurement result, and the synthetic error is less than 2°, which meets monitoring requirements for the guard plate.