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Next: Conclusions Up: Extracting Curvilinear Features from Previous: The User Interface

Results

Figure 2 is part of an image containing a large river feature. The river surface is light grey and the surrounding urban areas and river banks are darker grey.

Figure 3 shows the result of using the rough digitising tool to track the boundaries of the river. The extracted paths are superimposed in white over the original image.

In this example the river boundary is identified by the change in intensity between the river surface and the river bank. To extract these features a Sobel edge detector was applied to the image to highlight the boundary and the rough digitising tool was used to track the resulting edge features.

This involves selecting points along the path of the edge feature. If the edge is strong only a few points are needed to accurately digitise a complete path. If the edge is indistict the user has to select points that are closer together in order to provide the tool with more guidance.


  
Figure 2: Broad River Image
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Figure 3: Extracted Broad River Features
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\centerline{\psfig{figure=river_ovl.ps,width=3.0in}}
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Figure 4: Narrow River Image
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Figure 5: Extracted Narrow River Feature
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\centerline{\psfig{figure=nepal2_ovl.ps,width=2.0in}}
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Figure 4 shows the course of a river in an area of Nepal. The image is in infra red, so the river shows up dark against the relatively warm land.

In this example the user has only selected two points on the river, near the top and bottom of the image. The path found by the algorithm is shown superimposed in white on the image in figure 5. In this case, in order to find the dark path, the cost function minimises the sum of the intensities along the path. It can be seen that the course of the river has been successfully located along its length.


next up previous
Next: Conclusions Up: Extracting Curvilinear Features from Previous: The User Interface
Mark Dobie
1999-03-04