Error-controllable subdivision surface image vectorization method

Abstract

The invention discloses an error-controllable subdivision surface image vectorization method, and the method comprises the following steps: 1), detecting the edge features of an image, and obtaining an initial image feature line segment with the one-pixel width; 2), constructing an initial grid based on the image features, and marking the image features in the grid; 3), simplifying the initial grid, and constructing a base grid maintaining the image features; 4), carrying out the error-controllable Loop subdivision surface fitting, and obtaining a control grid; 5), carrying out the rasterization vector expression. The method can obtain a better vector image through a raster image. If the error of an initial reconstruction result cannot meet the demands of a user, the method can measure the error of a vectorized reconstruction image and an original image. The adaptive subdividing of the base grid is used for achieving a specific error in a certain range, thereby achieving the error controllability. The method employs the subdivision surface technology for image vectorization, and aims at the conversion of the raster image to the vector expression meeting the error requirements, and has the practical value.

Description

technical field [0001] The invention relates to the field of image vectorization using subdivision surface technology, in particular to an error-controllable subdivision surface image vectorization method, which aims to convert a raster image into a vector representation that meets error requirements. Background technique [0002] In the computer, there are two typical representations of images, one is raster image, also known as bitmap, bitmap image, and the other is vector image, also known as vector graphics and vector representation. Compared with raster images, vector graphics have many advantages, such as small storage capacity, easy editing, resolution-independent, etc. With the diversification of display devices and the improvement of resolution, the advantages of vector images have become increasingly prominent. The purpose of image vectorization is to convert bitmap images into vector images. [0003] In recent years, scholars have proposed many different image v...

AI Technical Summary

Problems solved by technology

But this algorithm also has some problems. First, this method models the discontinuity of color values ​​on both sides of the image edge by splitting the sub-pixel edge. The vectorization result depends too much on the base grid, and the error cannot be controlled

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