Towards Error-controllable Image Vectorization Based on Subdivision Surfaces

To improve the reconstruction quality of vectorization images, an error-controllable vectorization algorithm based on subdivision surfaces is proposed. Given an image to be vectorized, it first extracts feature lines, constructs a dense initial mesh, and simplifies the initial mesh using the quadric error metric algorithm to obtain a base mesh. A Loop subdivision surface with sharp feature settings is then employed to fit the color height fields of the image. Finally, it adaptively inserts new control points into the control mesh for reducing the approximating error. Experimental results show that the proposed algorithm can obviously improve the quality of the reconstructed images compared to the original fitting results, and achieve error-controllable fitting to some extent.