基于纹理提取和优化的图像矢量化方法
毕业论文关键词 矢量化 纹理提取 K-Means 聚类 扩散曲线 B 样条拟合 颜色渲染
Title Image vector method based on texture extraction and optimization
Abstract Vector graph is the image that uses the geometry feature to draw the image, with points, lines, or some key points color storing image information. Compared to on a series of color dot matrix composition pattern bitmap, vector graph with small files, infinite zoom without mosaic or distortion, can be easily programmed and geometry editing, and is conducive to the 3D reconstruction or animation editing based on vector graphics. In the application of CAD/CAM software, 3D printing technology, medical, animation and aerospace and other fields has clear practical significance, and in every application, it is usually possible to have only bitmap data. In view of this, this paper is to keep the bitmap features and the advantages of the premise, based on bitmap image of the vector method of discussion. However, the texture of the slightly more complex bitmap image, our numerical experiments show that the traditional image vector method is directly used to combine color rendering system and the results are not satisfactory. Therefore, this article begins from the bitmap image features. First of all, through the analysis and comparison of various texture extraction algorithm, selection method of texture image pre processing is completed, the original bitmap processing part of structure and texture, and then to the two parts in order processing. Secondly, the vector and color rendering of the main structure is processed by using the method of diffusion curve. After the pre segmentation image processing, its conversion to grayscale, detected by Canny edge extraction of image edge and detail information of the, K-means clustering and B spline fitting these curves information, extracts pixel values of the key points. Based on the vector information, color rendering is performed by solving the diffusion curve of Poisson equation. Finally, the texture of the original image is processed, and then fused with the smooth part of the vector, and the final vector image is obtained. The results of numerical experiments show the rationality and validity of the method.