Start » Filter Reference » Computer Vision » Hough Transform » DetectSingleCircle
Module: | FoundationBasic |
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Finds the strongest circle of a given radius in the input image.
Applications
Detection of a circular or close-to-circular object like a hole, pin, pill or particle.
Name | Type | Range | Description | |
---|---|---|---|---|
inImage | Image | Input image | ||
inRoi | Region* | Input region of interest | ||
inRadius | Real | 0.0 - | Circle's radius | |
inMinScore | Real | 0.0 - | Minimum matching score | |
inEdgeThreshold | Real | Minimum accepted edge magnitude | ||
outCircle | HoughCircle? | Found circle | ||
diagGradientMagnitudeImage | Image | Visualized gradients magnitude of an input image | ||
diagScoreImage | Image | Calculated score for each pixel of an input image |
Description
The operation detects circular object of given radius (in pixels) in the inImage using the Hough Transform approach.
Hints
- Connect an input image to the inImage input.
- Define the expected circle radius on the inRadius input. Use the Ruler tool on an image preview if you are not sure.
- Set inEdgeThreshold to define the minimum strength of edges that will be taken into account. Verify this value with the diagGradientMagnitudeImage output.
- Experimentally set the inMinScore value, whose meaning is more or less "the number of pixels voting for a particular object location".
Examples
Description of usage of this filter can be found in examples and tutorial: Counting Saw Teeth.
Hardware Acceleration
This operation supports automatic parallelization for multicore and multiprocessor systems.
Complexity Level
This filter is available on Advanced Complexity Level.
Filter Group
This filter is member of DetectCircles filter group.
See Also
- DetectMultipleCircles – Finds circles of a given radius in the input image using Hough Transform.
- DetectLines – Finds lines in an image using Hough Transform.
- DetectPaths – Finds a specified shape in an image using Hough Transform.
- DetectSegments – Finds segments in an image using Hough Transform.