Nowadays, vector map content is widely used in the areas of life, science and the military. Due to the fact that vector maps bring great value and that their production process is expensive, a large volume of vector map data is attacked, stolen and illegally distributed by pirates. Thus, vector map data must be encrypted before being stored and transmitted in order to ensure the access and to prevent illegal copying. This paper presents a novel perceptual encryption algorithm for ensuring the secured storage and transmission of vector map data. Polyline data of vector maps are extracted to interpolate a spline curve, which is represented by an interpolating vector, the curvature degree coefficients, and control points. The proposed algorithm is based on encrypting the control points of the spline curve in the frequency domain of discrete cosine transform. Control points are transformed and selectively encrypted in the frequency domain of discrete cosine transform. They are then used in an inverse interpolation to generate the encrypted vector map. Experimental results show that the entire vector map is altered after the encryption process, and the proposed algorithm is very effective for a large dataset of vector maps.

Detailed high capacity vector maps must be compressed effectively for transmission or storage in Web GIS (geographic information system) and mobile GIS applications. In this paper, we present a polyline compression method that consists of polyline feature-based hybrid simplification and second derivative-based data compression. The polyline hybrid simplification function detects the feature points from a polyline using DP, SF, and TF algorithms, and divides the polyline into sectors using these feature points. It then simplifies the sectors using an algorithm to determine the minimum area difference among the DP, SF, and TF results. The polyline data compression method segments the second derivatives of the simplified polylines into integer and fractional parts. The integer parts are compressed using the minimum bounding box of the layer to determine the broad position of the object. The fractional parts are compressed using hierarchical precision levels. Experimental results verify that our method has higher simplification and compression efficiency than conventional methods and produces good quality compressed maps.

In this paper, we have proposed a new method of observing walking traces, which can observe people's indoor movement for life-logging. Particularly emphasized new techniques in this paper are methods to detect locations, where walking directions are changed, by analyzing azimuth orientations measured by an orientation sensor of an Android mobile device, and to decide walking traces by a map matching with a vector map. The experimental evaluation has shown that the proposed method can determine the correct paths of walking traces.

On a topographical map of civil engineering, there are various enclosed areas, for instance, rice fields, meadows, buildings, roads, walls, regional boundaries and so on. Before a software system such as road planer is run, it is necessary to extract these various regions and features, and to transform them to 3D data. The automatic extraction and classification of all of them on a screen are difficult and very time-consuming. It is better to combine the automatic recognition with interactive operation. It is obvious that interaction is easily done when vector date of maps is applied. On the other hand, the vector data is much less than the raster data of the same map. This paper proposes a practical solution for understanding of vector maps, including two major methoeds; ditching (DIrected Track stretCHING) method for open regions (e.g., roads, slopes and walls etc.) and inward tracing method for bounded regions (e.g., various fields).