- What is the disadvantage of Hough transform?
- How Hough transform is used for boundary shape detection?
- Why is the Hough transform efficient?
What is the disadvantage of Hough transform?
Limitations. The Hough transform is only efficient if a high number of votes fall in the right bin, so that the bin can be easily detected amid the background noise. This means that the bin must not be too small, or else some votes will fall in the neighboring bins, thus reducing the visibility of the main bin.
How Hough transform is used for boundary shape detection?
Hough transform can detect lines, circles and other structures if their parametric equation is known. It can give robust detection under noise and partial occlusion • It can give robust detection under noise and partial occlusion. Borders between the regions are • Borders between the regions are straight lines.
Why is the Hough transform efficient?
The HT implementation defines a mapping from the image points into an accumulator space (Hough space). The mapping is achieved in a computationally efficient manner, based on the function that describes the target shape. This mapping requires much less computational resources than template matching.