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Abstract

Three-dimensional surface model based on edge collapse improvement model data compression algorithm

Author(s): Renshang Zhang

Along with the computer technology and the rapid development of the three dimensional imaging software and hardware technology, the three digital technology is more and more get people's attention and application. But limited graphics graphics processing power and the spread of the media has been affected by the network bandwidth, rely on increasing hardware input, not enough to solve the problem, must adopt corresponding algorithm of 3 d surface model data is compressed, can fundamentally solve this defect. Although some common compression algorithms and tools can be used to reduce the three-dimensional geometric data volume, but the efficiency is not ideal, or for some specific application doesn't fit, 3 d model with previous audio (1 d), image (2 d), video (2 d + time) of the three different media types, 3 d mesh model also show any bending, parametric characteristics of complex and the lack of a continuous nature, and define the rules of various properties on the surface of the model are sampling, which makes the classical orthogonal analysis tool 3 d geometry signals cannot be directly used for processing. Therefore, looking for a new algorithm to efficiently express 3 d model is needed. Proposed in this paper Garland compression algorithm based on surface model, this paper proposes a surface data compression algorithm based on edge collapse, and the algorithm based on quadratic error metrics calculate the edge collapse cost, and guidelines to determine the order of edge collapse, on the basis of test methods to judge the legitimacy of the shrinkage is half space, the boundary of the surface by the algorithm and model with internal synchronous compression in the region and in the case of high compression ratio can not only ensure the geometrical characteristic of the original model, and also can effectively guarantee the quality of the compression model.


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Citations : 875

BioTechnology: An Indian Journal received 875 citations as per Google Scholar report

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