Research on Image Fuzzy Edge Processing Based on Subpixel and Ramer-Douglas-Peucker Algorithm

This paper establishes an image fuzzy edge gray distribution model, and the image contour edge is interpolated by polynomial interpolation. After the image preprocessing, such as image grayscale, filtering, and noise reduction, the input image is preprocessed. The Gaussian edge model synthesizes discrete pixel curves or surfaces, and the traditional Canny edge method is extracted. The Sobel operator is used to calculate the gradient image, and then the gradient image is processed. Gradient direction polynomial interpolation to achieve sub-pixel edge localization of target edges. Considering the size measurement of the irregular shape of the image, the coordinate value of the sub-pixel edge contour length is calculated based on the idea of the micro-element method. Considering that the image contains straight lines and curves, it ensures that the shape of the original image contour is not changed as much as possible through a specific Sampling rate, using the curvature characteristics of the three to calculate the curvature of the data point. This paper uses the Ramer-Douglas-Peucker algorithm to down-sample multiple contour curves into similar curves with smaller points.