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ScanSingleRidge


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

Syntax

C++
C#
 
void avl::ScanSingleRidge
(
	const avl::Image& inImage,
	const ScanMap& inScanMap,
	const RidgeScanParams& inRidgeScanParams,
	avl::Selection::Type inRidgeSelection,
	atl::Optional<const avl::LocalBlindness&> inLocalBlindness,
	atl::Conditional<avl::Ridge1D>& outRidge,
	avl::Profile& diagBrightnessProfile,
	avl::Profile& diagResponseProfile
)

Parameters

Name Type Default Description
inImage const Image& Input image
inScanMap const ScanMap& Data precomputed with CreateScanMap
inRidgeScanParams const RidgeScanParams& Parameters controlling the ridge extraction process
inRidgeSelection Selection::Type Selection::​Best Selection mode of the resulting ridge
inLocalBlindness Optional<const LocalBlindness&> NIL Defines conditions in which weaker ridges can be detected in the vicinity of stronger ridges
outRidge Conditional<Ridge1D>& Found ridge
diagBrightnessProfile Profile& Extracted image profile
diagResponseProfile 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.

Hints

  • Adjust inRidgeScanParams.RidgeWidth to the expected thickness of the ridge (in pixels).
  • Define inRidgeScanParams.RidgePolarity to detect a particular ridge type, and only that type.
  • If no ridge is found, try decreasing inRidgeScanParams.MinMagnitude.
  • For difficult cases try different settings of the inRidgeScanParams.RidgeOperator parameter.

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