Generalised Hough Transform
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The Generalized Hough Transform, introduced by D.H. Ballard in 1981, was a modification of the Hough Transform using the principle of template matching [1]. This modification enables the Hough Transform to be used not only to detect an object described with an analytic equation (e.g. line, circle, etc), but also to detect an arbitrary object described with its model.
The problem of finding the object (described with a model) in the image can be solved by finding the model's position in the image. In the Generalized Hough Transform, the problem of finding the model's position is transformed into a problem of finding the transformation parameter that maps the model onto the image. As long as we know the value of the transformation parameter, then the position of the model in the image can be determined.
[edit] References
- ^ D.H. Ballard, "Generalizing the Hough Transform to Detect Arbitrary Shapes", Pattern Recognition, Vol.13, No.2, p.111-122, 1981
