ClassesClasses | | Operators

lines_facetlines_facetLinesFacetLinesFacet (Operator)

Name

lines_facetlines_facetLinesFacetLinesFacet — Detection of lines using the facet model.

Signature

lines_facet(Image : Lines : MaskSize, Low, High, LightDark : )

Herror lines_facet(const Hobject Image, Hobject* Lines, const Hlong MaskSize, double Low, double High, const char* LightDark)

Herror T_lines_facet(const Hobject Image, Hobject* Lines, const Htuple MaskSize, const Htuple Low, const Htuple High, const Htuple LightDark)

void LinesFacet(const HObject& Image, HObject* Lines, const HTuple& MaskSize, const HTuple& Low, const HTuple& High, const HTuple& LightDark)

HXLDCont HImage::LinesFacet(Hlong MaskSize, const HTuple& Low, const HTuple& High, const HString& LightDark) const

HXLDCont HImage::LinesFacet(Hlong MaskSize, double Low, double High, const HString& LightDark) const

HXLDCont HImage::LinesFacet(Hlong MaskSize, double Low, double High, const char* LightDark) const

static void HOperatorSet.LinesFacet(HObject image, out HObject lines, HTuple maskSize, HTuple low, HTuple high, HTuple lightDark)

HXLDCont HImage.LinesFacet(int maskSize, HTuple low, HTuple high, string lightDark)

HXLDCont HImage.LinesFacet(int maskSize, double low, double high, string lightDark)

Description

The operator lines_facetlines_facetLinesFacetLinesFacetLinesFacet can be used to extract lines (curvilinear structures) from the image ImageImageImageImageimage. The extracted lines are returned in LinesLinesLinesLineslines as subpixel precise XLD-contours. The parameter LightDarkLightDarkLightDarkLightDarklightDark determines, whether bright or dark lines are extracted.

The extraction is done by using the facet model, i.e., a least squares fit, to determine the parameters of a quadratic polynomial in x and y for each point of the image. The parameter MaskSizeMaskSizeMaskSizeMaskSizemaskSize determines the size of the window used for the least squares fit. Larger values of MaskSizeMaskSizeMaskSizeMaskSizemaskSize lead to a larger smoothing of the image, but can lead to worse localization of the line. The parameters of the polynomial are used to calculate the line direction for each pixel. Pixels which exhibit a local maximum in the second directional derivative perpendicular to the line direction are marked as line points. The line points found in this manner are then linked to contours. This is done by immediately accepting line points that have a second derivative larger than HighHighHighHighhigh. Points that have a second derivative smaller than LowLowLowLowlow are rejected. All other line points are accepted if they are connected to accepted points by a connected path. This is similar to a hysteresis threshold operation with infinite path length (see hysteresis_thresholdhysteresis_thresholdHysteresisThresholdHysteresisThresholdHysteresisThreshold). However, this function is not used internally since it does not allow the extraction of subpixel precise contours.

The gist of how to select the thresholds in the description of lines_gausslines_gaussLinesGaussLinesGaussLinesGauss also holds for this operator. A value of Sigma = 1.5 there roughly corresponds to a MaskSizeMaskSizeMaskSizeMaskSizemaskSize of 5 here.

The extracted lines are returned in a topologically sound data structure in LinesLinesLinesLineslines. This means that lines are correctly split at junction points.

lines_facetlines_facetLinesFacetLinesFacetLinesFacet defines the following attributes for each line point:

'angle'"angle""angle""angle""angle":

The angle of the direction perpendicular to the line

'response'"response""response""response""response":

The magnitude of the second derivative

These attributes can be queried via the operator get_contour_attrib_xldget_contour_attrib_xldGetContourAttribXldGetContourAttribXldGetContourAttribXld.

Attention

The smaller the filter size MaskSizeMaskSizeMaskSizeMaskSizemaskSize is chosen, the more short, fragmented lines will be extracted. This can lead to considerably longer execution times.

Note that filter operators may return unexpected results if an image with a reduced domain is used as input. Please refer to the chapter Filters.

Execution Information

Parameters

ImageImageImageImageimage (input_object)  singlechannelimage objectHImageHImageHobject (byte / int1 / int2 / uint2 / int4 / real)

Input image.

LinesLinesLinesLineslines (output_object)  xld_cont-array objectHXLDContHXLDContHobject *

Extracted lines.

MaskSizeMaskSizeMaskSizeMaskSizemaskSize (input_control)  integer HTupleHTupleHtuple (integer) (int / long) (Hlong) (Hlong)

Size of the facet model mask.

Default value: 5

List of values: 3, 5, 7, 9, 11

LowLowLowLowlow (input_control)  number HTupleHTupleHtuple (real / integer) (double / int / long) (double / Hlong) (double / Hlong)

Lower threshold for the hysteresis threshold operation.

Default value: 3

Suggested values: 0, 0.5, 1, 2, 3, 4, 5, 8, 10

Typical range of values: 0 ≤ Low Low Low Low low ≤ 20

Recommended increment: 0.5

Restriction: Low >= 0

HighHighHighHighhigh (input_control)  number HTupleHTupleHtuple (real / integer) (double / int / long) (double / Hlong) (double / Hlong)

Upper threshold for the hysteresis threshold operation.

Default value: 8

Suggested values: 0, 0.5, 1, 2, 3, 4, 5, 8, 10, 12, 15, 18, 20, 25

Typical range of values: 0 ≤ High High High High high ≤ 35

Recommended increment: 0.5

Restriction: High >= 0 && High >= Low

LightDarkLightDarkLightDarkLightDarklightDark (input_control)  string HTupleHTupleHtuple (string) (string) (HString) (char*)

Extract bright or dark lines.

Default value: 'light' "light" "light" "light" "light"

List of values: 'dark'"dark""dark""dark""dark", 'light'"light""light""light""light"

Example (HDevelop)

* Detection of lines in an aerial image
read_image(Image,'mreut4_3')
lines_facet(Image,Lines,5,3,8,'light')
dev_display(Lines)

Example (C)

/* Detection of lines in an aerial image */
read_image(&Image,"mreut4_3");
lines_facet(Image:&Lines:5,3,8,"light");
disp_xld(Lines,WindowHandle);

Example (HDevelop)

* Detection of lines in an aerial image
read_image(Image,'mreut4_3')
lines_facet(Image,Lines,5,3,8,'light')
dev_display(Lines)

Example (HDevelop)

* Detection of lines in an aerial image
read_image(Image,'mreut4_3')
lines_facet(Image,Lines,5,3,8,'light')
dev_display(Lines)

Example (HDevelop)

* Detection of lines in an aerial image
read_image(Image,'mreut4_3')
lines_facet(Image,Lines,5,3,8,'light')
dev_display(Lines)

Complexity

Let A be the number of pixels in the domain of ImageImageImageImageimage. Then the runtime complexity is O(A*MaskSize).

The amount of temporary memory required is dependent on the height H of the domain of ImageImageImageImageimage and the width W of ImageImageImageImageimage. Let S = W*H, then lines_facetlines_facetLinesFacetLinesFacetLinesFacet requires at least 55*S bytes of temporary memory during execution.

Result

lines_facetlines_facetLinesFacetLinesFacetLinesFacet returns 2 (H_MSG_TRUE) if all parameters are correct and no error occurs during execution. If the input is empty the behaviour can be set via set_system(::'no_object_result',<Result>:)set_system("no_object_result",<Result>)SetSystem("no_object_result",<Result>)SetSystem("no_object_result",<Result>)SetSystem("no_object_result",<Result>). If necessary, an exception is raised.

Possible Successors

gen_polygons_xldgen_polygons_xldGenPolygonsXldGenPolygonsXldGenPolygonsXld

Alternatives

lines_gausslines_gaussLinesGaussLinesGaussLinesGauss

See also

bandpass_imagebandpass_imageBandpassImageBandpassImageBandpassImage, dyn_thresholddyn_thresholdDynThresholdDynThresholdDynThreshold, topographic_sketchtopographic_sketchTopographicSketchTopographicSketchTopographicSketch

References

A. Busch: “Fast Recognition of Lines in Digital Images Without User-Supplied Parameters”. In H. Ebner, C. Heipke, K.Eder, eds., “Spatial Information from Digital Photogrammetry and Computer Vision”, International Archives of Photogrammetry and Remote Sensing, Vol. 30, Part 3/1, pp. 91-97, 1994.

Module

2D Metrology


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