FEATURE-BASED TEXTURE SYNTHESIS AND EDITING USING VORONOI DIAGRAMS Muath Sabha Department of Multimedia Technology Arab American University-Jenin, Palestine email: firstname.lastname@example.org Philip Dutr´ e Department of Computer Science Katholieke Universiteit Leuven, Belgium email: email@example.com erating a similar distribution in the target texture and that is explained in the subsections 3.1 and 3.2. (2) The second and major component, which we consider the main contribution in our work, is the shape of the patch and its placement in the target texture, which is discussed in subsection 3.3. Texture editing is an important application of our technique, and that is explained in 3.4. In section 4, we show some results generated from different textures, followed by discussion. Finally, section 5 concludes this work and puts some recommendations for future work.
In this paper, we present a technique to synthesize featured textures easily and interactively. The main idea is to synthesize a new texture by copying irregular patches from the source to the target texture, each of which contains a complete feature. The interior part of the feature is not touched while the cutting and stitching is performed on the background texture between the features. The technique starts by selecting a feature in the source texture by the user, after which the algorithm ﬁnds the positions of other features, generates a similar distribution of features, and ﬁnally synthesizes the target texture by copying and stitching patches of the target’s Voronoi cellular shapes from the source texture. The technique is fast enough to be used interactively to edit textures in a simple and easy way. KEY WORDS Texture editing, Voronoi diagrams, Image synthesis.
Computer graphics applications often use textures to decorate virtual objects to increase realism without modifying geometric details. In recent years, texture synthesis has been a useful tool to generate large textures starting from a sample texture. It is also used to ﬁll holes in damaged pictures, or to generate limitless textures in interactive applications like games and simulators applications. Samplebased texture synthesis schemes are based on analyzing the sample texture to create visually similar images. From a sample image taken from nature by a photographer or made by an artist, our technique generates an inﬁnite aperiodic texture by copying irregular patches from the sample to the target texture. Figure 1 outlines the stages of the technique. Using a suitable editor, the user can modify the generated texture easily. The user can add, move, remove and merge features from different textures as shown in ﬁgure 6. This paper starts by a quick overview of the recent contributions and most related to our work in the ﬁeld of texture synthesis in section 2. In section 3, our technique will be explained in detail. Our work is composed of two main components, (1) the ﬁrst is analyzing the source texture and extracting the features’ positions, and then gen1
There are various sample-based texture synthesis approaches which start from an exemplar to generate new textures: Texture Synthesis by Analysis generates a new texture depending on statistics extracted from the sample texture [2, 15, 27]. Pixel-based Texture Synthesis techniques depend on neighborhood matching to generate the target texture pixel by pixel. For each pixel, the already synthesized spatial neighborhood is compared to exemplar neighborhoods to identify the most elaborate pixels [6, 24, 19, 11, 8]. Most of the pixel-based techniques follow the Markov Random Field model. Texture morphing  works better with Pixel-Based techniques, and  uses the texton mask for texture morphing.  and  used the pixel-based approach to synthesize texture on surfaces, and  used a a data structure called jump-map to synthesize pixels over surfaces. Efros and Freeman , Xu et al....
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