Abstract
In light of the current problems including coarseness, visible cracks, difficult data organisation, and the expensive memory requirements of the current texture methods, this paper mainly focuses on efficient organisation, linearised memory compression and seamless texture mapping between scanned Citrus sinensis images and point cloud information. Position and colour gradient based top-down splitting is proposed to simplify and organise the texture as texel descriptors to avoid both over-simplification and under-simplification. A Quadtree Morton and Z-order based linearised coding strategy is presented to compress the memory space of our texel descriptor based texture. A Gaussian Markov random field scheme was designed to smooth the ‘cracks’ between neighbouring texels. The simulated results on eight Citrus sinensises show that our simplification method reduces the texture memory requirements by 81.3 % over the original image, and 50 % over conventional simplification. The compression scheme also showed a 61.7 % improvement over the ordinary Morton code. Finally, the Gaussian Markov random field scheme makes the texture mapping smoother in comparison with other methods.
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Acknowledgment
The authors would like to thank the Fundamental Research Funds for the Central Universities (No. 2014YB067, 2452015199, 2452015195), the National High Technology Research and Development Program of China (863 Program.2013AA10230402), the National High Technology Research and Development Program of China (2013BAD15B02), the Scholarship Council and Scientific Research Foundation for Ph. D from Northwest Agriculture & Forest University of China (2014BSJJ060), for financial support provided.
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Yang, H., Chang, J., Geng, N. et al. Texture organisation and mapping on Citrus sinensis point cloud. Multimed Tools Appl 76, 14711–14732 (2017). https://doi.org/10.1007/s11042-016-3998-6
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DOI: https://doi.org/10.1007/s11042-016-3998-6