In this paper, we investigate the impact of intensity edge maps (IEMs) on the segmentation of noisy range images. Two edge-based segmentation algorithms are considered. The first is a watershed-based segmentation technique and the other is the scan-line grouping technique. Each of these algorithms is implemented in two different forms. In the first form, an IEM is fused with the range edge map prior to segmentation. In the second form, the range edge map alone is used. The performance of each algorithm, with and without the use of the IEM information, is evaluated and reported in terms of correct segmentation rate. For our experiments, two sets of real range images are used. The first set comprises inherently noisy images. The other set is composed of images with varying levels of artificial, additive Gaussian noise. The experimental results indicate that the use of IEMs can significantly improve edge-based segmentation of noisy range images. Considering these results, it seems that segmentation tasks involving range images captured by noisy scanners would benefit from the use of IEM information. Additionally, the experiments indicate that higher quality edge information can be obtained by fusing range and intensity edge information.
|Number of pages||10|
|Journal||Proceedings of SPIE - The International Society for Optical Engineering|
|State||Published - Jan 1 2000|
|Event||Three-Dimensional Image Capture and Applications III - San Jose, CA, USA|
Duration: Jan 24 2000 → Jan 25 2000