2D hair strands generation based on template matching

Hair modelling is an important part of many applications in computer graphics. Since 2D hair strands represent the information of the hair shape and the feature of the hairstyles, the generation of 2D hair strands is an essential part for image-based hair modelling. In this paper, we present a novel algorithm to generate 2D hair strands based on a template matching method. The method first divides a real hairstyle input image into sub-images with the predefined size. For each sub-image, an orientation map is estimated using Gabor filter and the orientation feature is presented by the orientation histogram. Then it matches the orientation histograms between each sub-image and template images in our database. Based on the matching results, the sub-images are replaced by the corresponding manual stroke images to give a clear representation of 2D hair strands. The result is refined by connecting the strands between adjacent sub-images. Finally, based on the control points defined on the 2D hair strands, the spline representation is applied to obtain smooth hair strands. Experimental results indicate that our algorithm is feasible.