Integration of Visible Image and LIDAR Altimetric Data for Semi-Automatic Detection and Measuring the Boundari of Features

This paper presents a new method for detecting the features using LiDAR data and visible images. The proposed features detection algorithm has the lowest dependency on region and the type of sensor used for imaging, and about any input LiDAR and image data, including visible bands (red, green and blue) with high spatial resolution, identify features with acceptable accuracy. In the proposed approach, detecting the features by using the object-based analysis theory as the main approach has been performed. Also two different approaches and innovations in order to increase “Level of Automation” (LoA) and level of accuracy and precision in detecting process have been proposed and performed. The first approach uses visible and LiDAR data independently in order to resolve the problem of high-dependencies between data in the existing algorithms. The second proposed method has been suggested in order to the detection of vegetation regions. Among the characteristics of this method it can be mentioned that there is no need to use the infrared band in the image data and also there is no need to intensify information of the laser returns. By assessing the results of available data classification, the determined overall accuracy of the proposed method on average, about vegetation regions is 98 % which shows the highest value compared with other features. The proposed method about other features also achieves acceptable accuracy.