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vision.HoughTransform System object

Package: vision

Find lines in images via Hough transform


    Note:   The vision.HoughTransform System object will be removed in a future release. Use the hough function with equivalent functionality instead.

The HoughTransform object finds lines in images via Hough transform. The Hough transform maps points in the Cartesian image space to curves in the Hough parameter space using the following equation:


Here, rho denotes the distance from the origin to the line along a vector perpendicular to the line, and theta denotes the angle between the x-axis and this vector. This object computes the parameter space matrix, whose rows and columns correspond to the rho and theta values respectively. Peak values in this matrix represent potential straight lines in the input image.

    Note:   Starting in R2016b, instead of using the step method to perform the operation defined by the System object™, you can call the object with arguments, as if it were a function. For example, y = step(obj,x) and y = obj(x) perform equivalent operations.


H = vision.HoughTransform returns a Hough transform System object, H, that implements the Hough transform to detect lines in images.

H = vision.HoughTransform(Name,Value) returns a Hough transform object, H, with each specified property set to the specified value. You can specify additional name-value pair arguments in any order as (Name1, Value1,...,NameN,ValueN).

H = vision.HoughTransform(THETARES, RHORES,'Name',Value,...) returns a Hough transform object, H, with the ThetaResolution property set to THETARES, the RhoResolution property set to RHORES, and other specified properties set to the specified values.

Code Generation Support
Supports MATLAB® Function block: Yes
System Objects in MATLAB Code Generation (MATLAB Coder).
Code Generation Support, Usage Notes, and Limitations.



Theta resolution in radians

Specify the spacing of the Hough transform bins along the theta-axis in radians, as a scalar numeric value between 0 and pi/2. The default is pi/180.


Rho resolution

Specify the spacing of the Hough transform bins along the rho-axis as a scalar numeric value greater than 0. The default is 1.


Enable theta and rho outputs

Set this property to true for the object to output theta and rho values. The default is false.


Data type of output

Specify the data type of the output signal as double, single, or Fixed point. The default is double.

 Fixed-Point Properties


stepOutput parameter space matrix for binary input image matrix
Common to All System Objects

Create System object with same property values


Expected number of inputs to a System object


Expected number of outputs of a System object


Check locked states of a System object (logical)


Allow System object property value changes


expand all

Read the intensity image.

    I = imread('circuit.tif');

Create an edge detector, Hough transform, local maxima finder, and Hough lines objects.

    hedge = vision.EdgeDetector;
    hhoughtrans = vision.HoughTransform(pi/360,'ThetaRhoOutputPort', true);
    hfindmax = vision.LocalMaximaFinder(1,	'HoughMatrixInput', true);
    hhoughlines = vision.HoughLines('SineComputation','Trigonometric function');
Warning: The vision.EdgeDetector will be removed in a future release. Use the
edge function with equivalent functionality instead. 
Warning: The vision.HoughTransform will be removed in a future release. Use the
hough function with equivalent functionality instead. 

Find the edges in the intensity image

 	BW = step(hedge, I);

Run the edge output through the transform

	[ht, theta, rho] = step(hhoughtrans, BW);

Find the location of the max value in the Hough matrix.

 	idx = step(hfindmax, ht);

Find the longest line.

 	linepts = step(hhoughlines, theta(idx(1)-1), rho(idx(2)-1), I);

View the image superimposed with the longest line.

   imshow(I); hold on;
   line(linepts([1 3])-1, linepts([2 4])-1,'color',[1 1 0]);


This object implements the algorithm, inputs, and outputs described on the Hough Transform block reference page. The object properties correspond to the block parameters.

Introduced in R2012a

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