This paper presents a new algorithm 'Method of the Square' (MS) for automatic image vectorization, which is implemented and tested here against some classical vectorization algorithms (ArcInfo, Contour Fitting and Sparse Pixel Vectorization). The comparison between these algorithms is performed by using widely accepted performance metrics introduced by Wenyin and Dov Dori (such as pixel recovery index pixel -PRI, pixel detection rate -D p , false pixel detection rate -F p ) and shows that the algorithms discussed here achieve comparable performances. The experimental results qualify the proposed MS algorithm as a cheaper alternative for image vectorization.

Within the European Politics for Geographic Information, geographic information represents a complex part in continuous development of informational society having a wide range of applicability. This can be categorized into: spatial, geographic information and descriptive, qualitative information. These two types of data can be integrated in the same information management system by a Geographic Informational System. (GIS).With the final aim of realizing an infrastructure of spatial data at European and global level, the implementation of the most recent acquisition techniques is pursued as well as the processing and the integration of data in an effective system of geospatial data.The image from the satellite is composed of information and superposed noise coming from a number of noise sources like the noise produced by the sensor during the acquisition or the digitized photographic document. Any operation which processes each and every pixel independently on the value of neighboring pixels results in undifferentiated increase of the level of the noise and of the information in the image. In this way it is necessary that the resulting images suffer a proper process of minimization of the level of the noise.One of the first issues approached in the article is targeted at the definition of sounds ( the Gaussian noise, uniform noise, salt and pepper noise) and at the way of applying each type of special filter used for their elimination ( ordinate filters and mediation filters) After the application of specific methods for the processing and transformation of images, the authors have defined the organization structure of data depending on the requirements of a project. Thus, grouped workspace will be created for each set of data which will be structured during the technologic process.The second part of the article deals with techniques to obtain these data sets depending on the type of data for which it was defined. Information on how to obtain data sets specific to metropolitan networks, data sets for analyzing and visualizing 3D, the data set for Web Application, cadastral data set and the data set for the creation of the digital model of land will be presented. For instance, the Ras Mos data set is a data set of the raster type which has the role to stock images resulted from the ortho-rectifying, compression and mosaication.The third part of the article presents the geometric processing of images in the process that take place at the level of digital photogrammetric systems. These processing are done by the soft for digital photogrammetric application to bring to coincidence the plan of stereo images with the plan in the field.In conclusion, it should be remarked that the images obtained suffer a complex technological process so that one can obtain the geometric position of topographic objects in the field with a high degree of accuracy from their content. Of course, it must be emphasized that during the whole acquisition process and the process of data acquisition, errors may occur that cumulate. These errors ...