Difference between revisions of "Hough Transform"
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| + | [[Category:How to Guides: Technical]] | ||
| + | [[Category:IGVC]] | ||
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| + | This algorithm is implemented as the '''LinearHoughTransform2''' filter for the [[ImageFilterDemo]] program. | ||
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A good description is on [http://homepages.inf.ed.ac.uk/rbf/HIPR2/hough.htm this page]. | A good description is on [http://homepages.inf.ed.ac.uk/rbf/HIPR2/hough.htm this page]. | ||
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== Cons == | == Cons == | ||
| − | * | + | * Designed for detecting ''straight'' lines, making it tricky to use for curved lines - which will probably be common |
| − | |||
* Designed to detect ''lines'' as opposed to detecting ''line segments'' | * Designed to detect ''lines'' as opposed to detecting ''line segments'' | ||
* Computationally expensive (when compared to simple filters) | * Computationally expensive (when compared to simple filters) | ||
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== Output == | == Output == | ||
* A list of the positions/orientations of the lines detected in the input image | * A list of the positions/orientations of the lines detected in the input image | ||
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| + | == Issues with the Current Implementation == | ||
| + | * The current implementation does not work well with input images containing no lines. This, however, is due to the way that Hough output is thresholded - the Hough algorithm itself still works well. | ||
== Pictures == | == Pictures == | ||
Latest revision as of 20:51, 5 February 2020
This algorithm is implemented as the LinearHoughTransform2 filter for the ImageFilterDemo program.
A good description is on this page.
Wikipedia also has its own Hough Transform article.
Pros
- Able to detect dashed lines
Cons
- Designed for detecting straight lines, making it tricky to use for curved lines - which will probably be common
- Designed to detect lines as opposed to detecting line segments
- Computationally expensive (when compared to simple filters)
Input
- A binary/grayscale image hilighting the line-pixels in the input image
Output
- A list of the positions/orientations of the lines detected in the input image
Issues with the Current Implementation
- The current implementation does not work well with input images containing no lines. This, however, is due to the way that Hough output is thresholded - the Hough algorithm itself still works well.
Pictures
