Scalable Vector Graphics (svg) In The Description Of The Tcm Fingerprint Data

The technology of Chinese traditional medicine fingerprint identification is widely used in the field of the produce and research of Chinese traditional medicine, especially on the aspect of Quality Control, it is very important. But, there isn't an unified standard, the formats of Chinese traditional medicine fingerprint identification document are of a wide variety. These formats each have their advantages and disadvantages. Numerous formats not only put trouble to the development of the software on the Chinese traditional medicine fingerprint identification station, but also impede the sharing of Chinese traditional medicine fingerprint identification data. This thesis aims at exploring a kind of excellent format for describing Chinese traditional medicine fingerprint identification document, thereby unify the disordered situation.SVG (Scalable Vector Graphics) is a format of vector graph based on text recommended by W3C (Word Wide Web Consortium), that has the attribute of Scalable, flexible and usable. It's main advantages are: high quality, independent text, few storage, powerful interoperability. Therefore, SVG is very suitable for describing Chinese traditional medicine fingerprint identification. This thesis presents a solution to describe Chinese traditional medicine fingerprint identification based on SVG. It contains modal design, building and transform.Semantic Web is a hot field recently. It is a kind of Web using a method to describe data able to be understood by computer. It develops the ability of Web. Semantic Web can not only display the data, but also reason according to the semantic content of the data. Therefore, the data on Web should be semantic. Finally, this thesis deeply researches the semantic content of Chinese traditional medicine fingerprint identification based on SVG, presents a method of referencing RDF (Resource Description Framework) descriptions in SVG document to realize the semantic content of Chinese traditional medicine fingerprint identification based on SVG.