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ScanSingleStripe

Header:	FIL.h
Namespace:	fil

Locates the strongest pair of edges across a given path.

Syntax

void fil::ScanSingleStripe
(
	const fil::Image& inImage,
	const ScanMap& inScanMap,
	const StripeScanParams& inStripeScanParams,
	fil::Selection::Type inStripeSelection,
	ftl::Optional<const fil::LocalBlindness&> inLocalBlindness,
	ftl::Conditional<fil::Stripe1D>& outStripe,
	fil::Profile& diagBrightnessProfile,
	fil::Profile& diagResponseProfile
)

Parameters

Name	Type	Default	Description
inImage	const Image&		Input image
inScanMap	const ScanMap&		Data precomputed with CreateScanMap
inStripeScanParams	const StripeScanParams&		Parameters controlling the stripe extraction process
inStripeSelection	Selection::Type	Selection::Best	Selection mode of the resulting stripe
inLocalBlindness	Optional<const LocalBlindness&>	NIL	Defines conditions in which weaker edges can be detected in the vicinity of stronger edges
outStripe	Conditional<Stripe1D>&		Found stripe
diagBrightnessProfile	Profile&		Extracted image profile
diagResponseProfile	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 stripe (i.e. a pair of opposite-polarity edges running across the path) of the given characteristics. If there is no such stripe then the outputs are set to NIL.

Hints

Define inStripeScanParams.StripePolarity to detect a particular edge type, and only that type.
If no stripe is found, try decreasing inStripeScanParams.MinMagnitude. Verify this with the values on the diagResponseProfile output.
If consecutive edges are closer than 6 pixels apart, change inStripeScanParams.ProfileInterpolation to Quadratic3.

Examples

ScanSingleStripe locates the strongest stripe using a scan map representing the scan path above.

Remarks

Read more about Local Coordinate Systems in Machine Vision Guide: Local Coordinate Systems.

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.