You are here: Start » AVL.NET » AVL.ScanSingleEdge(AvlNet.Image, AvlNet.ScanMap, AvlNet.EdgeScanParams, AvlNet.Selection, AvlNet.LocalBlindness, AvlNet.Edge1D?, AvlNet.Profile, AvlNet.Profile)
AVL.ScanSingleEdge(AvlNet.Image, AvlNet.ScanMap, AvlNet.EdgeScanParams, AvlNet.Selection, AvlNet.LocalBlindness, AvlNet.Edge1D?, AvlNet.Profile, AvlNet.Profile)
Locates the strongest transition between dark and bright pixels along a given path.
| Namespace: | AvlNet |
|---|---|
| Assembly: | AVL.NET.dll |
Syntax
public static void ScanSingleEdge( AvlNet.Image inImage, AvlNet.ScanMap inScanMap, AvlNet.EdgeScanParams inEdgeScanParams, AvlNet.Selection inEdgeSelection, AvlNet.LocalBlindness inLocalBlindness, out AvlNet.Edge1D? outEdge, out AvlNet.Profile diagBrightnessProfile, out AvlNet.Profile diagResponseProfile )
Parameters
- inImage
- Type: AvlNet.Image
Input image - inScanMap
- Type: AvlNet.ScanMap
Data precomputed with CreateScanMap - inEdgeScanParams
- Type: AvlNet.EdgeScanParams
Parameters controlling the edge extraction process - inEdgeSelection
- Type: AvlNet.Selection
Selection mode of the resulting edge - inLocalBlindness
- Type: AvlNet.LocalBlindness
Defines conditions in which weaker edges can be detected in the vicinity of stronger edges, or null. - outEdge
- Type: System.Nullable<AvlNet.Edge1D>
Found edge - diagBrightnessProfile
- Type: AvlNet.Profile
Extracted image profile - diagResponseProfile
- Type: AvlNet.Profile
Profile of the edge (derivative) operator response
Description
The operation scans the image using inScanMap previously generated from a scan path and locates the strongest edge perpendicular to the path. If the strongest edge is weaker than inEdgeScanParams.minMagnitude then the outputs are set to NIL.
Examples
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ScanSingleEdge locates the strongest edge using a scan map representing the scan path above.
Remarks
For more information about local coordinate systems please refer to the following article.
This filter is a part of the 1D Edge Detection toolset. For a comprehensive introduction to this technique please refer to 1D Edge Detection and 1D Edge Detection - Subpixel Precision chapters of our Machine Vision Guide.


