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Bark Texture Synthesis by Patch-Based Sampling

Author: CaoZuo
Tutor: WangZhongZhi
School: Beijing Forestry University
Course: Applied Computer Technology
Keywords: Texture Synthesis Bark texture Texture gradient Edge blending
CLC: TP391.41
Type: Master's thesis
Year: 2008
Downloads: 34
Quote: 1
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Abstract


Today's graphics can achieve the simulation of high - quality trees , but also the lack of meticulous research in the bark texture simulation . Bark surface texture with rich details and trunk in different parts of the texture texture may occur natural gradient , To a true analog bark texture of these effects is not easy . This paper presents a photorealistic bark texture synthesis method . The method is based on the idea of block texture synthesis can be based on a few pieces of bark - like map texture , whole bark texture synthesis part of the trunk , at the same time alleviate the burden of the staff manual collection entire bark texture . The synthesis method is divided into two steps the horizontal synthetic \Application \In order to further the realistic simulation of bark surface texture texture gradient effect , \The method by controlling the synthesis of probability , effectively between different texture bark texture gradient , thus successfully bark gradually change the effect of the analog seasoned tender . In the synthesis process , in order to enhance the realism of the effect , the article also taking into account the analog of the bark surface scarring results . Samples and edge blending to achieve a function to add a scar in the bark texture surface , in order to effectively achieve bark scarring effect simulation. The experiments show that the proposed method can effectively generate with the growth variation realistic bark texture , to meet the needs of photorealistic rendering .

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device
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