🔷Point Cloud Edge Extraction - Unordered (Legacy)

Functional Description

This operator is used to extract edge points from input unordered point clouds with normals. It identifies edges by analyzing normal vector direction differences between each point in the point cloud and its neighboring points, with options to use K-nearest neighbor (KNN) or radius search (RADIUS) to define neighborhoods. If the maximum angle difference between a point and points in its neighborhood exceeds the set "Edge Angle Threshold", that point is identified as an edge point. The operator can also choose whether to adjust output edge points' normal vector directions.

Usage Scenarios

Suitable for scenarios requiring compatibility with legacy workflows.
Feature Extraction: Extract contours or geometric edges of unordered point clouds.
Visualization: Highlight object contours

Input Output

Input

Point Cloud with Normals: Input must be unordered point clouds or point cloud lists containing normal vector information.

CalculateEdgeDisorderOld input

Output

Point Cloud Edges: Point cloud list composed of extracted edge points. Output point cloud contains only points identified as edges and preserves their original coordinate and normal vector information (normals may be adjusted).

CalculateEdgeDisorderOld output

Parameter Description

Edge Angle Threshold

Parameter Description

Normal vector angle difference threshold for determining whether a point is an edge point.

Parameter Adjustment

The operator calculates angle differences between each point and its neighboring points' normal vectors. If the maximum value among these angle differences exceeds the threshold set here, that point is considered an edge point.

Decreasing threshold: More sensitive to normal changes, will extract more edges.
Increasing threshold: Will only identify points with very dramatic normal changes as edges, extracting fewer edges.

Parameter Range

[0, 180], Default value: 90, Unit: degrees

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CalculateEdgeDisorderOld output

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Edge Angle Threshold=10

Edge Angle Threshold=90

Edge Angle Threshold=180

Adjust Edge Normals

Parameter Description

Choose whether to adjust normal vectors after extracting edge points.

Parameter Adjustment

On (Default): Recalculate and adjust normal vectors of identified edge points to make them as perpendicular as possible to edge direction and point in consistent direction (outward or inward).

CalculateEdgeDisorderOld output

Off: Preserve original normal vectors of edge points.

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Neighbor Search Method

Parameter Description

Choose method for defining neighborhood range of each point.

Parameter Adjustment

Count Search (Default): Find the nearest K points to current point as neighborhood, meaning always take fixed number of neighboring points regardless of actual distances between these points. K value is specified by "Neighbor Search Count" parameter.

CalculateEdgeDisorderOld output

Radius Search: Search with fixed physical distance as radius, find all points within this range. Radius value is specified by "Neighbor Search Radius" parameter.

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Neighbor Search Count

Parameter Description

Effective when "Neighbor Search Method" selects "Count Search".

Parameter Adjustment

Controls number of neighboring points:

Fewer count: More sensitive to local detail edge changes, but also more sensitive to noise, prone to misjudgment in sparse regions.
More count: Insensitive to noise with smoother results. Larger count means greater computational load, suitable for low-density or non-uniform point clouds.

Parameter Range

[0, 100000], Default value: 20

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CalculateEdgeDisorderOld 10

Neighbor Search Count=10

Neighbor Search Count=20

Neighbor Search Count=100

Neighbor Search Radius

Parameter Description

Effective when "Neighbor Search Method" selects "Radius Search".

Parameter Adjustment

Controls spatial range of neighborhood for angle difference calculation:

Smaller radius: Only considers very close neighboring points, can more sharply capture local details and edge changes, but more sensitive to noise. Sparse regions may have insufficient neighbors causing unstable estimation.
Larger radius: Covers wider neighborhood, computation results are smoother and more robust, suitable for low-density or non-uniform point clouds, but may mask details and blur edges.

Parameter Range

[0, 1000], Default value: 10

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