close_edges_lengthclose_edges_lengthCloseEdgesLengthCloseEdgesLength (Operator)


close_edges_lengthclose_edges_lengthCloseEdgesLengthCloseEdgesLength — Close edge gaps using the edge amplitude image.


close_edges_length(Edges, Gradient : ClosedEdges : MinAmplitude, MaxGapLength : )

Herror close_edges_length(const Hobject Edges, const Hobject Gradient, Hobject* ClosedEdges, const Hlong MinAmplitude, const Hlong MaxGapLength)

Herror T_close_edges_length(const Hobject Edges, const Hobject Gradient, Hobject* ClosedEdges, const Htuple MinAmplitude, const Htuple MaxGapLength)

void CloseEdgesLength(const HObject& Edges, const HObject& Gradient, HObject* ClosedEdges, const HTuple& MinAmplitude, const HTuple& MaxGapLength)

HRegion HRegion::CloseEdgesLength(const HImage& Gradient, Hlong MinAmplitude, Hlong MaxGapLength) const

static void HOperatorSet.CloseEdgesLength(HObject edges, HObject gradient, out HObject closedEdges, HTuple minAmplitude, HTuple maxGapLength)

HRegion HRegion.CloseEdgesLength(HImage gradient, int minAmplitude, int maxGapLength)


close_edges_lengthclose_edges_lengthCloseEdgesLengthCloseEdgesLengthCloseEdgesLength closes gaps in the output of an edge detector, and thus tries to produce complete object contours. This operator expects as input the edges (EdgesEdgesEdgesEdgesedges) and amplitude image (GradientGradientGradientGradientgradient) returned by typical edge operators, such as edges_imageedges_imageEdgesImageEdgesImageEdgesImage or sobel_ampsobel_ampSobelAmpSobelAmpSobelAmp.

Contours are closed in two steps: First, one pixel wide gaps in the input contours are closed, and isolated points are eliminated. After this, open contours are extended by up to MaxGapLengthMaxGapLengthMaxGapLengthMaxGapLengthmaxGapLength points by adding edge points until either the contour is closed or no more significant edge points can be found. A gradient is regarded as significant if it is larger than MinAmplitudeMinAmplitudeMinAmplitudeMinAmplitudeminAmplitude. The neighboring points examined as possible new edge points are the point in the direction of the contour and its two adjacent points in an 8-neighborhood. For each of these points, the sum of its gradient and the maximum gradient of that points three possible neighbors is calculated (look ahead of length 1). The point with the maximum sum is then chosen as the new edge point.


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


EdgesEdgesEdgesEdgesedges (input_object)  region(-array) objectHRegionHRegionHobject

Region containing one pixel thick edges.

GradientGradientGradientGradientgradient (input_object)  singlechannelimage objectHImageHImageHobject (byte / uint2)

Edge amplitude (gradient) image.

ClosedEdgesClosedEdgesClosedEdgesClosedEdgesclosedEdges (output_object)  region(-array) objectHRegionHRegionHobject *

Region containing closed edges.

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

Minimum edge amplitude.

Default value: 16

Suggested values: 5, 8, 10, 12, 16, 20, 25, 30, 40, 50

Typical range of values: 1 ≤ MinAmplitude MinAmplitude MinAmplitude MinAmplitude minAmplitude ≤ 255

Minimum increment: 1

Recommended increment: 1

Restriction: MinAmplitude >= 0

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

Maximal number of points by which edges are extended.

Default value: 3

Suggested values: 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 15, 20, 30, 40, 50, 70, 100

Typical range of values: 1 ≤ MaxGapLength MaxGapLength MaxGapLength MaxGapLength maxGapLength ≤ 127

Minimum increment: 1

Recommended increment: 1

Restriction: MaxGapLength > 0 && MaxGapLength <= 127

Example (C)



close_edges_lengthclose_edges_lengthCloseEdgesLengthCloseEdgesLengthCloseEdgesLength returns 2 (H_MSG_TRUE) if all parameters are correct. If the input is empty the behavior 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 Predecessors

edges_imageedges_imageEdgesImageEdgesImageEdgesImage, sobel_ampsobel_ampSobelAmpSobelAmpSobelAmp, thresholdthresholdThresholdThresholdThreshold, skeletonskeletonSkeletonSkeletonSkeleton


close_edgesclose_edgesCloseEdgesCloseEdgesCloseEdges, dilation1dilation1Dilation1Dilation1Dilation1, closingclosingClosingClosingClosing


M. Üsbeck: “Untersuchungen zur echtzeitfähigen Segmentierung”; Studienarbeit, Bayerisches Forschungszentrum für Wissensbasierte Systeme (FORWISS), Erlangen, 1993.