2D Figure Pattern Mining
Keiji Gyohten, Hiroaki Kizu, Naomichi Sue · InTech eBooks · 2011
1.1 Background With the recent enhancement of desktop design environments, it has become easy for personal users to design graphical documents such as posters, flyers, slides, drawings, etc. These kinds of documents are usually produced by the applications like drawing softwares, which have the advantage that they can store and retrieve the drawing data electronically. By reusing parts of the stored drawing data, the users can design the graphical documents much more easily. However, generally, the stored data of many users is not shared, although this can be achieved by putting a drawing database. One reason is that it is difficult to retrieve desired figures from large amounts of drawing data in the database. Unlike in text search, the figure search will require enormous amounts of computation time because matching of the geometric primitives in the drawing data will cause their combinatorial explosion in 2D space. To address this problem, many approaches have been proposed recently. When users search the drawing database, they should conjure up the desired figures and design their 2D sketches as the keys. In case of retrieving general figures, such as electrical symbols and map symbols, there would be little difference between sketches of them drawn by different users, but it is impractical to make them visualize various objects and things and use the sketches as the keys. For example, in case of retrieving human figures, since the sketches of humans differ according to the users, not all of figures of humans will be able to be obtained from the drawing database. To cope with this problem, we need a technique that enables the applications to automatically present users with the list of figures considered to have any meaning. Users can specify a figure of the desired object or thing simply by selecting it from the list and then retrieve the desired figures from the database using it as the key.