The cascaded Hough transform as support for grouping and finding vanishing points and lines (original) (raw)
1997, Lecture Notes in Computer Science
AI-generated Abstract
The paper presents a novel approach using cascaded Hough transforms to efficiently group and identify vanishing points and lines in images. This method enhances the accuracy of detecting geometrical structures by leveraging statistical techniques to optimize the computational process, ultimately improving the quality of image analysis in applications like computer vision.
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Proceedings of International Conference on Image Processing, 1997
When using the original slope-intercept parameterisation for the Hough transform, the resulting parameter space actually corresponds to the dual space. Indeed, lines are transformed into points, and for every point there is also a corresponding line. This paper presents a way of exploiting this special property, by the introduction of the Cascaded Hough Transform, or CHT for short. This allows to look for the overall structure in an image, such as lines intersecting in a point or intersection points lying on a line. An interesting example is the detection of vanishing points and vanishing lines.
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