The Terrasolid software suite has many tools that support mobile mapping. Included in these is the capability to extract paint markings. This tool has been discussed in isolation in previous Tool Tips, but this article discusses a workflow, of which Find Paint Lines plays a leading role. The following steps are discussed:
- Correct intensity values
- Create intensity ortho
- Paint line extraction
As with all LIDAR processing, it is important for the data to be properly calibrated using such tools as Find Tie Line Match and Find Tie Line Fluctuations. Another important step is to classify the road points using the Hard Surface routine. Since this workflow will use point intensity values to detect the paint lines, then it is important to include all the points on the road surface for consideration to ensure that there is enough information for the routine to work. The Hard Surface routine will leave out many of these points since it only considers the median points in the road. Therefore, it is important to classify additional points on the road surface to ensure that the points are dense enough for paint line extraction. This can be accomplished using the Classify by Distance tool.
Once everything is calibrated and pre-classified, visually examine the data using the Color by Intensity Display Mode option (Figure 1). If the intensity values are not consistent then it would be necessary to correct them using tools in TerraMatch, such as the Find Intensity Correction, to establish distinguished paint markings.
Figure 1: Points viewed by intensity
In addition to viewing the points, an intensity ortho can be created to assist in visualization and validation of the extracted line work. The Export Raster Images tool using the Road Intensity option (Figure 2) is specifically designed to ensure connected paint lines along the alignment. This option differs from the usual intensity ortho option in that is uses a road alignment vector to directionally sample the intensity values, thereby resulting in a more desirable image of the road markings.
Figure 2: Road intensity ortho, including the ortho tiles and labels
Before moving on to the paint line extraction step, it is important to determine the intensity range that will be considered paint lines by the system. These values can be identified by using the Identify and Intensity Histogram commands. As an aside, the Intensity Histogram is an included example of how to create addon tools to leverage the built-in capabilities of TerraScan and expand them to create your own tools for LIDAR data.
Paint Line Extraction
For the paint lines to be extracted, the points representing them need to be uniquely classified. This is accomplished with the Classify by Intensity tool utilizing the intensity value range identified earlier. Next, the paint line points should be thinned to ensure similar spacing of the down track and cross track point spacing (Figure 3). If this is not accounted for, then the paint line extraction can favor one direction over the other, as systematically it easier to follow points of closer spacing than to cross larger gaps, skewing the results.
Figure 3: Cross track and down track have different densities.
With the paint line points classified and thinned appropriately, the Paint Line Extraction can proceed using the alignment vector to assist with the desired direction for the lines to be extracted. The process results in text files, which can then be read by TerraScan to generate the desired vectors into the MicroStation design file. This method enables the macro to be run through TerraSlave.
Figure 4: Paint lines found parallel to a selected alignment vector.
With the paint lines extracted (Figure 4), further analysis can determine where paint lines need to be added or repaired. In addition, these lines can be used as the input required for the semi-automatic extraction of the road centerline and edge of pavement vectors which are useful in further mobile mapping analysis. If you have any questions on this tool or associated workflow, please do not hesitate to contact us at email@example.com.