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A Ray Casting Accelerated Method of Segmented Regular Volume Data

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Advanced Research on Electronic Commerce, Web Application, and Communication (ECWAC 2011)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 144))

Abstract

The size of volume data field which is constructed by large-scale war industry product ICT images is large, and empty voxels in the volume data field occupy little ratio. The effect of existing ray casting accelerated methods is not distinct. In 3D visualization fault diagnosis of large-scale war industry product, only some of the information in the volume data field can help surveyor check out fault inside it. Computational complexity will greatly increase if all volume data is 3D reconstructed. So a new ray casting accelerated method based on segmented volume data is put forward. Segmented information volume data field is built by use of segmented result. Consulting the conformation method of existing hierarchical volume data structures, hierarchical volume data structure on the base of segmented information is constructed. According to the structure, the construction parts defined by user are identified automatically in ray casting. The other parts are regarded as empty voxels, hence the sampling step is adjusted dynamically, the sampling point amount is decreased, and the volume rendering speed is improved. Experimental results finally reveal the high efficiency and good display performance of the proposed method.

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© 2011 Springer-Verlag Berlin Heidelberg

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Zhu, M., Guo, M., Wang, L., Dai, Y. (2011). A Ray Casting Accelerated Method of Segmented Regular Volume Data. In: Shen, G., Huang, X. (eds) Advanced Research on Electronic Commerce, Web Application, and Communication. ECWAC 2011. Communications in Computer and Information Science, vol 144. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20370-1_2

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  • DOI: https://doi.org/10.1007/978-3-642-20370-1_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-20369-5

  • Online ISBN: 978-3-642-20370-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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