You are here: Start » AVL.NET » AVL.ScanSingleRidge(AvlNet.Image, AvlNet.ScanMap, AvlNet.RidgeScanParams, AvlNet.Selection, AvlNet.LocalBlindness, AvlNet.Ridge1D?, AvlNet.Profile, AvlNet.Profile)

AVL.ScanSingleRidge(AvlNet.Image, AvlNet.ScanMap, AvlNet.RidgeScanParams, AvlNet.Selection, AvlNet.LocalBlindness, AvlNet.Ridge1D?, AvlNet.Profile, AvlNet.Profile)

Locates the strongest dark or bright pixel peak along a given path.

Namespace:AvlNet
Assembly:AVL.NET.dll

Syntax


public static void ScanSingleRidge(
	AvlNet.Image inImage,
	AvlNet.ScanMap inScanMap,
	AvlNet.RidgeScanParams inRidgeScanParams,
	AvlNet.Selection inRidgeSelection,
	AvlNet.LocalBlindness inLocalBlindness,
	out AvlNet.Ridge1D? outRidge,
	out AvlNet.Profile diagBrightnessProfile,
	out AvlNet.Profile diagResponseProfile
)

Parameters

inImage
Type: AvlNet.Image
Input image
inScanMap
Type: AvlNet.ScanMap
Data precomputed with CreateScanMap
inRidgeScanParams
Type: AvlNet.RidgeScanParams
Parameters controlling the ridge extraction process
inRidgeSelection
Type: AvlNet.Selection
Selection mode of the resulting ridge
inLocalBlindness
Type: AvlNet.LocalBlindness
Defines conditions in which weaker ridges can be detected in the vicinity of stronger ridges, or null.
outRidge
Type: System.Nullable<AvlNet.Ridge1D>
Found ridge
diagBrightnessProfile
Type: AvlNet.Profile
Extracted image profile
diagResponseProfile
Type: AvlNet.Profile
Profile of the ridge operator response

Description

The operation scans the image using inScanMap previously generated from a scan path and locates the strongest ridge of the given characteristics. If there is no such ridge then the outputs are set to NIL.

Examples

ScanSingleRidge locates the strongest ridge 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.

See also