RESEARCH ON MACHINE VISION ROUNDNESS DETECTION METHOD BASED ON SNAKE ALGORITHM

In order to reduce the hardware cost of roundness detection, a machine vision-based roundness detection method is proposed. The basic idea of this roundness detection method is to divide roundness detection into two stages: coarse positioning and fine positioning. In the first stage, the Hough transform method is used to achieve rough localization of circular boundaries; In the second stage, the Snake algorithm is used to achieve precise positioning of circular boundaries. In the experimental verification stage, a circular instrument was used as the experimental object for experimental research, and a roundness detection effect evaluation method based on the least squares method was proposed. The experimental results show that the proposed method achieves ideal detection accuracy for circular features. Further selection of multi-attribute decision-making methods, decision tree methods, and support vector machine methods were compared with the proposed method for roundness detection, and the results showed that the proposed method can obtain higher accuracy roundness detection results.