Hough transform

The Hough transform is a feature extraction technique used in image analysis, computer vision, and digital image processing. The purpose of the technique is to find imperfect instances of objects within a certain class of shapes by a voting procedure.

1. How Hough transform is used for detection of lines in an image?
2. How does Hough Circle transform work?
3. How object recognition is done through Hough transform?

How Hough transform is used for detection of lines in an image?

If two edge points lay on the same line, their corresponding cosine curves will intersect each other on a specific (ρ, θ) pair. Thus, the Hough Transform algorithm detects lines by finding the (ρ, θ) pairs that have a number of intersections larger than a certain threshold.

How does Hough Circle transform work?

The circle Hough Transform (CHT) is a basic feature extraction technique used in digital image processing for detecting circles in imperfect images. The circle candidates are produced by “voting” in the Hough parameter space and then selecting local maxima in an accumulator matrix.

How object recognition is done through Hough transform?

In this paper we use Hough transform technique to identify the shape of the object by mapping the edge points of the image and also to identify the existing straight lines in the image. The Edge Detection Algorithm is applied to detect the edge points by the sharp or sudden change in intensity.