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Article type: Research Article
Authors: Yang, Hui Juna; b | Wang, Zhi Yaoa | Wang, Xina; * | Chang, Jianb | Xu, Jinga | Zhang, Jian Fengb | Chen, Canc | Zhang, Jian Junb
Affiliations: [a] College of Information Engineering the Attached High School, and Department of Foreign Languages, Northwest A&F University, Yangling, Shaanxi, China | [b] National Centre for Computer Animation, Bournemouth University, Poole, Dorset, UK | [c] Changzhou University, Changzhou, Jiangsu, China
Correspondence: [*] Corresponding author: Xin Wang, Department of Foreign Languages, Northwest A&F University, Yangling, Shaanxi, China. E-mail:303863040@qq.com
Abstract: The fruit images on points cloud acquired by the current 3D scanner from field will appear a visible seams, inconvenient data acquisition or taking large space due to unorganized background. We give a SAOW method to cope with the space efficiency and realistic effects of texture synthesis on pear point model. At first, a point-quadtree is proposed to simplify the pear image division. Then, an adaptive multi-granularity morton coding scheme are presented to optimizing the memory space of pear image. At last, weighted oversampling mixing method is mainly focused on texture quality of pear surface. As shown in the experiment results, our adaptive division makes the memory space decline dramatically about 90.7% than non-division and 92.9% than general division respectively; adaptive code scheme helps to reduce the memory to 72.1% of ordinary morton code; weighted oversampling keeps the mixed texture more real and smoothly than current methods.
Keywords: Texture division, texton, adaptive morton code, texture synthesis
DOI: 10.3233/JCM-170725
Journal: Journal of Computational Methods in Sciences and Engineering, vol. 17, no. 3, pp. 397-409, 2017
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