## 5 Discussion
In the proposed method the authors utilise functions of the SDK library allowing the acquisition of RAW data without the necessity to use external software. Comparing the time of raster generation using the proposed method and the original software it may be noticed that the proposed method is time-consuming, but it allows for preparation of RAW data, to generate raster images in the selected cartographic projection in order to automatically detect tie points, using detectors, such as FAST and SURF. Selection of those detectors resulted from preliminary tests, performed by the authors for other objects, such an open landscape [12] or historical interiors [37]. Differences in the approach relied upon the use of TLS data directly processed with the Z + F LaserControl application (they were not the RAW data), the scanner positions were similar to scenario A, and the castle ruins were the measured object. Tests performed in Reference [37] proved the correctness of operations of the SIFT detector. Due to time-consuming automatic searching for planes for orthoimages, it was decided to apply the Mercator projection. Earlier tests proved that, using spherical raster images, it is not possible to detect tie points on the ceiling. Due to the fact that the intensity of laser beam reflectance differs and it depends on the distance and the scanning angle, the same areas are characterised by the different intensity in different raster images. This influences the correctness and the number of initial tie points. Therefore, it is also necessary to perform the proposed initial filtration and orientation of tie points with the use of the RANSAC algorithm in the TLS registration process. When results presented in Tables 3 and 4 are analysed, it may be noticed that in the case of test sites of historical objects (Site I and II), the FAST, as well as the SURF algorithms detected the high number of possible tie points which quality turned to be low. Thus, the great number of tie points does not always prove the better process of point matching. This was also proved by the number of rejected points. In general, it may be stated that the best results were obtained for point clouds acquired with the limited angular resolution in the Mercator projection (Test site I). In the case of the full angular resolution, the best results were obtained for orthoimages (Test site II). In the case of Test sites III and IV, which were walls were smooth without architectural decorations, the number of detected tie points were considerably smaller. Paradoxically, despite the smaller number of points, the majority of them were not rejected in the data filtration process; this proves the correct matching of descriptors. For such room, it is recommended to use the spherical projection. The SURF and FAST detectors allow detecting the similar number of correct tie points. To perform the TLS data registration methodology based on raster images, the orientation of the same scans was performed using the target-based registration method in Z + F LaserControl software. It was performed on the same test sites where marked checked points were located (Table 12). When results presented in Table 12 are analysed, it may be noticed that the proposed method allow obtaining better accuracy for all cartographic projections for historical objects which are characterised by the high number of architectural details and diversified texture. In the case of Test site III (office room) the results are worse than in the case of utilisation of the target-based method, however, the error values allow to obtain the correct orientation when more points are used. In the case of Test site IV, the results obtained by means of the proposed method should be considered as an approximation of the orientation performed using the ICP method. Two different test sites were selected for the analysis of the distribution of natural control and check points.