How to resolve the algorithm Hough transform step by step in the Mathematica / Wolfram Language programming language
How to resolve the algorithm Hough transform step by step in the Mathematica / Wolfram Language programming language
Table of Contents
Problem Statement
Implement the Hough transform, which is used as part of feature extraction with digital images. It is a tool that makes it far easier to identify straight lines in the source image, whatever their orientation. The transform maps each point in the target image,
( ρ , θ )
{\displaystyle (\rho ,\theta )}
, to the average color of the pixels on the corresponding line of the source image (in
( x , y )
{\displaystyle (x,y)}
-space, where the line corresponds to points of the form
x cos θ + y sin θ
ρ
{\displaystyle x\cos \theta +y\sin \theta =\rho }
). The idea is that where there is a straight line in the original image, it corresponds to a bright (or dark, depending on the color of the background field) spot; by applying a suitable filter to the results of the transform, it is possible to extract the locations of the lines in the original image. The target space actually uses polar coordinates, but is conventionally plotted on rectangular coordinates for display. There's no specification of exactly how to map polar coordinates to a flat surface for display, but a convenient method is to use one axis for
θ
{\displaystyle \theta }
and the other for
ρ
{\displaystyle \rho }
, with the center of the source image being the origin. There is also a spherical Hough transform, which is more suited to identifying planes in 3D data.
Let's start with the solution:
Step by Step solution about How to resolve the algorithm Hough transform step by step in the Mathematica / Wolfram Language programming language
Package: Wolfram Language Image Processing System
Function: Radon[]
Syntax:
Radon[image, Method -> "Hough"]
Purpose:
The Radon[] function computes the Radon transform of an image, which is a projection of the image onto a set of parallel lines. The "Hough" method uses the Hough transform to compute the Radon transform, which is a more efficient algorithm than the standard method.
Inputs:
image: The image to be transformed.Method -> "Hough": Specifies that the Hough transform method should be used.
Outputs:
The output of the Radon[] function is a Radon transform of the input image. The Radon transform is a 2D array, where the rows correspond to the different projection angles and the columns correspond to the different distances from the center of the image.
Example:
The following code snippet shows how to compute the Radon transform of an image using the Hough method:
image = Import["image.jpg"];
radonTransform = Radon[image, Method -> "Hough"];
The radonTransform variable will contain the Radon transform of the image.
Additional Information:
The Radon transform is a useful tool for image processing tasks such as object detection, edge detection, and image reconstruction. The Hough transform is a more efficient algorithm for computing the Radon transform than the standard method, and it is often used in real-world applications.
Source code in the wolfram programming language
Radon[image, Method -> "Hough"]
You may also check:How to resolve the algorithm Multi-dimensional array step by step in the X86-64 Assembly programming language
You may also check:How to resolve the algorithm Loops/Nested step by step in the Racket programming language
You may also check:How to resolve the algorithm File input/output step by step in the Go programming language
You may also check:How to resolve the algorithm Cartesian product of two or more lists step by step in the Bracmat programming language
You may also check:How to resolve the algorithm Longest common subsequence step by step in the Sidef programming language