By Mingquan Zhou
"Digital maintenance expertise for Cultural historical past" discusses the know-how and techniques in electronic upkeep of cultural background. It covers themes in 5 significant parts: Digitization of cultural history; electronic administration within the cultural background maintenance; recovery concepts for inflexible strong relics; recovery strategies for work; electronic museum. it's also software examples for electronic protection of cultural heritage.
The booklet is meant for researchers, complicated undergraduate and graduate scholars in special effects and snapshot Processing in addition to Cultural history preservation.
Mingquan Zhou is a professor on the collage of data technological know-how and know-how, Beijing basic collage, China. Guohua Geng is a professor on the collage of data technology and know-how, Northwest college, Xi'an, China. Zhongke Wu is a professor on the collage of data technological know-how and expertise, Beijing general college, China.
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Extra info for Digital preservation technology for cultural heritage
Volume Rendering Volume Rendering is a technology that generates a two-dimensional image directly from a three-dimensional data ﬁeld. In real world, there are many scenes that can not be shown by simple faces, such as smoke, ﬁre, cloud, and mist. In this situation volume rendering is preferable. Compared with the surface rendering, volume rendering’s biggest advantage is that it can display the inner structure of the objects, which is also one of the most important reasons for it to be widely used.
In addition, due to the diﬃculty in controlling the scanning speed, multiple scans, and uneven sampling, the captured data is unevenly distributed and contains a lot of redundancy and some noise. Usually downsampling techniques are used to reduce of the number of sampling points in order to get the appropriate sampling density (usually evenly distributed). Alexa  used greedy iterative strategy to move the positions of sampling points in the original model, and ﬁnally got the sampling points distributed evenly throughout the surface of the model.
Registration Usually 3D scanning devices can only capture part of an object at a time. To get the whole data of an object, multiple scans are needed. As the multiview data are captured from diﬀerent coordinate systems, they must be registered to be transformed into one coordinate system. Iterative closest point algorithm (ICP) is popular in solving the problem of three-dimensional registration, which is a high-level free-form surface based registration method proposed by Besl and Mckay . It ﬁrst uses the Newton iterative algorithm or search algorithm to ﬁnd the nearest point-pairs between two datasets.