Plane target positioning based on reflection intensity and K-means clustering method

Plane target positioning is one of the important parts to process the data obtained by terrestrial laser scanner measurement. In order to reduce the influence on the accuracy of multiple-scan registration, coordinate system transformation and object aided location when extracting coordinates of the target centre, a new method was proposed based on the least square method, K-means clustering method and the reflection intensity at the scanning points. After theoretical analysis and experimental verification, the positioning data with high accuracy was achieved. There are four major steps to deal with the problem: firstly, to eliminate noise points by using the total least squares algorithm; secondly, to classify the region of scanning data based on the reflection intensity; thirdly, to extract the centre coordinates of each region by means of K-means clustering method; finally, to calculate the target centre coordinates according to the centre position each region. The results show that reliable positioning accuracy can be obtained at a certain distance by means of the proposed method. The deviation of the coordinates is in the order of sub-millimeters, and the distance deviation is also in the order of sub-millimeters. The research is helpful for coordinate extraction of plane target centers.