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Header: AVL.h
Namespace: avl
Module: FoundationLite

Extracts a binary image of pixel-precise continuous edges.

Applications: Consistent detection of pixels that belong to contours of variable or unpredictable shape, e.g. screw thread outline or a custom piece of textile.


void avl::DetectEdges
	const avl::Image& inImage,
	atl::Optional<const avl::Region&> inRoi,
	avl::EdgeFilter::Type inEdgeFilter,
	float inStdDevX,
	atl::Optional<float> inStdDevY,
	float inEdgeThreshold,
	float inEdgeHysteresis,
	float inMaxJoiningDistance,
	const int inMinBlobArea,
	avl::Image& outEdgesImage,
	avl::Image& diagGradientMagnitudeImage


Name Type Range Default Description
Input value inImage const Image& Image from which edges will be extracted
Input value inRoi Optional<const Region&> NIL Region of the image from which edges will be extracted
Input value inEdgeFilter EdgeFilter::Type Type of edge filter used for computing gradients
Input value inStdDevX float 0.0 - 2.0f Amount of horizontal smoothing used by the edge filter
Input value inStdDevY Optional<float> 0.0 - NIL Amount of vertical smoothing used by the edge filter (Auto = inStdDevX)
Input value inEdgeThreshold float 0.0 - 15.0f Sufficient edge strength; edges of that strength will always be detected
Input value inEdgeHysteresis float 0.0 - 5.0f Value by which the edge threshold is decreased for edge points neighboring with sufficiently strong edges
Input value inMaxJoiningDistance float 0.0 - 0.0f Maximal distance between edges that can be joined
Input value inMinBlobArea const int 0 - 1 Minimal area of an edge blob
Output value outEdgesImage Image& Image of found edges
Diagnostic input diagGradientMagnitudeImage Image& Visualization of the gradient magnitude

In-place Processing

This function supports in-place data processing - you can pass the same reference to inImage and outEdgesImage

Read more about In-place Computation.

Hardware Acceleration

This operation supports automatic parallelization for multicore and multiprocessor systems.