Abstract

The aim of this paper is to develop a laser line detection algorithm which reduces the uncertainties what are caused by the unknown laser line width on the laser scanner images. Due to the fact that different surfaces reflect light in different ways the laser line on captured images is not always with constant width. The line width is also depending of the laser optics used. In 3D laser line scanners a correct detection of laser line is essential, because the laser line extraction accuracy affects greatly the precision of the developed 3D laser scanner. In this paper a method to use different standard deviations for inverted second order Gaussian derivative convolution mask to find the optimal standard deviation for every line section has been proposed. The results show a great dependency between standard deviation of the convolution kernel and laser line width. The experiments show that the optimal standard deviation of the convolution kernel is not constant over the whole laser line. Furthermore the optimal standard deviation for every line section reduces the uncertainties that were caused by the unknown laser line width.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call