Experimental Results

To evaluate the performance of the proposed algorithm in segmenting range images of curved objects, a range image database of a number of objects possessing both planar and curved surfaces from different materials is created. The actual data and their segmented results are shown in the following figures.

Figure 1 - Samples of intensity (left), plotted range data (middle) and segmentation result of the proposed algorithm (right). SSC selected Model 8 (Plane model) for all of the visible sides of the icosahedron.

Figure 2 - Samples of intensity (left), plotted range data (middle) and segmentation result of the proposed algorithm (right). SSC selected model 5 for the cylinder perpendicular to the xy plane (surface 4) and model 3 for the cylinder parallel to the xy plane (surface 5). For surface 6, which is a simple plan, model 8 is chosen by SSC.

Figure 3 - Samples of intensity (left), plotted range data (middle) and segmentation result of the proposed algorithm (right). SSC selected model 5 for the cylinder perpendicular to the xy plane (surface 2) and model 3 for the cylinder parallel to the xy plane (surface 3).

Figure 4 - Samples of intensity (top-left), plotted range data (top-right) and segmentation result of the proposed algorithm (bottom-left) and of UB algorithm (bottom-right). This result illustrates that the proposed algorithm can detect the similarity between two similar cylinders correctly. SSC selected model 3 for the cylinders parallel to the xy plane. The underlying surface models of all planar surfaces are chosen to be model 8 (plane).

Figure 5- Samples of intensity (top-left), plotted range data (top-right) and segmentation result of the proposed algorithm (bottom-left) and of UB algorithm (bottom-right). Although the range data contains substantial noise and invalid data, as shown in the plotted range image, the proposed algorithm has accurately segmented the scene. For surface 13, which is a cylinder perpendicular to the xy plane the model selected is model 5. For all of the planar surfaces, SSC has correctly selected model 8 as the underlying model.

Figure 6 - Samples of intensity (top-left), plotted range data (top-right) and segmentation result of the proposed algorithm (bottom-left) and of UB algorithm (bottom-right). The SSC has selects model 5 for the perpendicular cylinders to the xy plane (surface 16 and surface 15) model 8 for all the planar sections. Surface 17 has two separated planar parts and they are correctly joined together by the proposed technique.

Figure 7- A sample from the K2T range image database: intensity image (left)and segmentation results using the proposed algorithm (right). This image contains cylindrical, general quadratic and planar surfaces.

Figure 8- A sample from the K2T range image database: intensity image (left) and segmentation results using the proposed algorithm (right). The shadow of the doorknob is segmented separately.


 

Top

  1. Index
  2. Surface Selection Criterion (SSC)
  3. Characteristics of SSC
  4. Parametric Curved Surface Range Segmentation algorithm

 

By Niloofar Gheissari and Alireza Bab-Hadiashar

May 2004