Using Reversible Steganography Algorithm to Embed Metadata in Vector Maps

Vector maps are the fuel of many Geographic Information System (GIS) applications. Metadata, which is the data about vector maps, are introduced to provide the details of the vector maps. The usage of metadata is still facing some problems. Especially the storage of metadata is a problem that needs to be resolved. This paper presents an internal metadata storage mechanism for solving metadata storage problem by using a reversible steganographic algorithm to embed metadata in vector maps. Experimental results show that this method provides a solution for metadata embedding with high capacity but low distortion. The capacity of metadata embedding is 2(n-2) bits, where n is the amount of vertices of vector maps. To the best of our knowledge, our method provides the highest capaicty achieved in the literature of steganograhy for vector maps. In considering to the capacity required by the metadata elements of ISO 19115 metadata standard that we have adapted in this paper, a vector map should has at least 5458 vertices so that all mandatory and conditional metadata elements can be embedded in the vector map. Since the conditional elements should not be embedded alone, a vector map should has at least 1998 vertices so that the mandatory metadata elements can be embedded and integrated with the vector map. Experimental results also show that there is an insignificantly difference between the original and the recovery map, which is less than 3.41E-11 of the root mean square error (RMSE) and is imperceptible to the human visual system. Surely, the accuracy of recovery maps satisfies the requirements of all GIS applications development. Meanwhile, our method is robust against the affine transformation including translation, rotation, uniform scaling, and their combinations.