You are here: Start » Function Reference » 1D Edge Detection » CreateScanMap

CreateScanMap

Header:	AVL.h
Namespace:	avl

Precomputes a data object that is required for fast 1D edge detection.

Syntax

void avl::CreateScanMap
(
	const avl::ImageFormat& inImageFormat,
	const avl::Path& inScanPath,
	atl::Optional<const avl::CoordinateSystem2D&> inScanPathAlignment,
	int inScanWidth,
	avl::InterpolationMethod::Type inImageInterpolation,
	avl::ScanMap& outScanMap,
	atl::Optional<avl::Path&> outAlignedScanPath = atl::NIL,
	atl::Array<avl::Path>& diagSamplingPoints,
	float& diagSamplingStep
)

Parameters

Name	Type	Range	Default	Description
inImageFormat	const ImageFormat&			Dimensions, depth and pixel type of the image on which edge detection will be performed
inScanPath	const Path&			Path along which the scan is performed
inScanPathAlignment	Optional<const CoordinateSystem2D&>		NIL	Adjusts the scan path to the position of the inspected object
inScanWidth	int	1 -	5	Width of the scan field in pixels
inImageInterpolation	InterpolationMethod::Type		Bilinear	Interpolation method used for extraction of image pixel values
outScanMap	ScanMap&			Optimized data object required for 1D edge detection
outAlignedScanPath	Optional<Path&>		NIL	Transformed input path
diagSamplingPoints	Array<Path>&			Array of paths each one containing the sampling points that contributes to a single value of the extracted profile
diagSamplingStep	float&			Used distance between consecutive sampling points on the scan path

Optional Outputs

The computation of following outputs can be switched off by passing value atl::NIL to these parameters: outAlignedScanPath.

Description

The operation creates a scan map from a given inScanPath. The scan map can be later used by other 1D Edge Detection filters.

The optional parameter inScanPathAlignment defines a transform to be performed on the inScanPath so that the actual scan path (outAlignedScanPath) is adjusted to the position of the object, typically detected by one of Template Matching filters.

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.

Remarks