Research on Forklift Detection of Forklift Blade Based on Machine Vision

In order to solve the shortcomings of the manual visual measurement method used for checking forklift blade detachment, this paper developed a machine vision-based identification method to realize the timely detachment of forklift shovel teeth. A double threshold binarization method based on HSV color space is proposed. The impurity region is removed by using the fusion feature of the shovel tooth in the binary image, thereby further extracting the bucket region. In the scrap tooth missing detection phase, it is determined whether the tooth is missing by the principle of similarity between the area of the tooth area and the area template. The simulation results of the algorithm using shovel image in MATLAB show that the algorithm maintains high recognition accuracy and provide an effective solution for forklift shovel detection.