visionhdl.EdgeDetector

Find edges of objects

expand all in page

Description

visionhdl.EdgeDetector finds the edges in a grayscale pixel stream using the Sobel, Prewitt, or Roberts method. The object convolves the input pixels with derivative approximation matrices to find the gradient of pixel magnitude along two orthogonal directions. It then compares the sum of the squares of the gradients to a configurable threshold to determine if the gradients represent an edge. The Sobel and Prewitt methods calculate the gradient in horizontal and vertical directions. The Roberts method calculates the gradients at 45 and 135 degrees.

The object returns a binary image, as a stream of pixel values. A pixel value of 1 indicates that the pixel is an edge. You can optionally enable output of the gradient values in the two orthogonal directions at each pixel.

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.

Construction

ED = visionhdl.EdgeDetector returns a System object, ED, that detects edges using the Sobel method.

ED = visionhdl.EdgeDetector(Name,Value) returns a System object, ED, with additional options specified by one or more Name,Value pair arguments. Name is a property name and Value is the corresponding value. Name must appear inside single quotes (''). You can specify several name-value pair arguments in any order as Name1,Value1,...,NameN,ValueN. Properties not specified retain their default values.

Properties

Method

Edge detection algorithm.

Specify 'Sobel', 'Prewitt', or 'Roberts' method.

Default: 'Sobel'

BinaryImageOutputPort

Enable the Edge output of the step method.

When this property is true, the step method returns a binary pixel value representing whether the object detected an edge at each location in the frame.

Default: true

GradientComponentOutputPorts

Enable the G1 and G2 outputs of the step method.

When this property is true, the step method returns two values representing the gradients calculated in two orthogonal directions at each pixel. Set the data type for this argument in the GradientDataType property.

Default: false

ThresholdSource

Source for the gradient threshold value that indicates an edge.

Set this property to 'Input port'to set the threshold as an input argument to the step method. When this property is set to 'Property', set the threshold in the Threshold property.

Default: 'Property'

Threshold

Gradient threshold value that indicates an edge, specified as a numeric scalar value.

The object compares the square of this to the sum of the squares of the gradients. The object casts this value to the data type of the gradients. This property applies when you set ThresholdSource to 'Property'.

Default: 20

LineBufferSize

Specify a power of two that accommodates the number of active pixels in a single horizontal line.

Choose a power of two that accommodates the number of active pixels in a horizontal line. If you specify a value that is not a power of two, the object uses the next largest power of two. The object allocates (N - 1)-by-LineBufferSize memory locations to store the pixels, where N is the number of lines in the differential approximation matrix. If you set the Method property to 'Sobel'or 'Prewitt', then N is 3. If you set the Method property to 'Roberts', then N is 2.

Default: 2048

PaddingMethod

Select one of these methods for padding the boundary of the input image. For more information about these methods, see Edge Padding.

  • 'Symmetric' — Set the value of the padding pixels to mirror the edge of the image. This option prevents edges from being detected at the boundaries of the active frame.

  • 'None' — Exclude padding logic. The object does not set the pixels outside the image frame to any particular value. This option reduces the hardware resources used by the object and the blanking required between frames but affects the accuracy of the output pixels at the edges of the frame. To maintain pixel stream timing, the output frame is the same size as the input frame. However, to avoid using pixels calculated from undefined padding values, mask off the KernelSize/2 pixels around the edge of the frame for downstream operations. For details, see Increase Throughput with Padding None.

Default: 'Symmetric'

RoundingMethod

Rounding mode used for fixed-point operations.

The object uses fixed-point arithmetic for internal calculations when the input is any integer or fixed-point data type. This option does not apply when the input data type is single or double.

Default: Floor

OverflowAction

Overflow action used for fixed-point operations.

The object uses fixed-point arithmetic for internal calculations when the input is any integer or fixed-point data type. This option does not apply when the input data type is single or double.

Default: Wrap

GradientDataType

Data type for the gradient output values, specified as numerictype(signed,WL,FL), where WL is the word length and FL is the fraction length in bits.

  • 'Full precision' (default) — Use full-precision rules based on the data type of the pixelIn argument of the step method, and the coefficients of the derivative approximation matrices.

  • 'custom' — Use the data type defined in theCustomGradientDataType property.

CustomGradientDataType

Data type for the gradient output values, specified as numerictype(signed,WL,FL), where WL is the word length and FL is the fraction length in bits.

Default: numerictype(1,8,0)

Methods

stepDetect edges at an image pixel
Common to All System Objects
release

Allow System object property value changes

Examples

collapse all

Open Live Script

Detect edges in a thumbnail image using the Sobel method.

Import a test image. 

frmInput = imread('rice.png');
[frmActivePixels,frmActiveLines] = size(frmInput);
figure
imshow(frmInput)
title 'Input Image'

Create a serializer and specify the size of inactive pixel regions.

frm2pix = visionhdl.FrameToPixels(...
      'NumComponents',1,...
      'VideoFormat','custom',...
      'ActivePixelsPerLine',frmActivePixels,...
      'ActiveVideoLines',frmActiveLines,...
      'TotalPixelsPerLine',frmActivePixels+10,...
      'TotalVideoLines',frmActiveLines+10,...
      'StartingActiveLine',6,...     
      'FrontPorch',5);

Create an edge detection object with the default property values. The default detection method is Sobel.

edgeDetectSobel = visionhdl.EdgeDetector();

Speed up simulation by enabling a simulation mode that uses code generation for the System object. 

edgeDetectSobel.simulateUsing('Code generation');

Serialize the test image using the object you created. pixIn is a vector of intensity values. ctrlIn is a vector of control signal structures. Preallocate vectors for the output signals.

Note: This syntax runs only in R2016b or later. If you are using an earlier release, replace each call of an object with the equivalent step syntax. For example, replace myObject(x) with step(myObject,x).

[pixIn,ctrlIn] = frm2pix(frmInput);

[~,~,numPixelsPerFrame] = getparamfromfrm2pix(frm2pix);
ctrlOut = repmat(pixelcontrolstruct,numPixelsPerFrame,1);
edgeOut = false(numPixelsPerFrame,1);

For each pixel in the stream, compute whether it represents an edge.

for p = 1:numPixelsPerFrame  
   [edgeOut(p),ctrlOut(p)] = edgeDetectSobel(pixIn(p),ctrlIn(p));
end

Create a deserializer with a format matching that of the serializer. Use the deserializer to convert the output pixel stream to an image frame.

pix2frm = visionhdl.PixelsToFrame(...
      'NumComponents',1,...
      'VideoFormat','custom',...
      'ActivePixelsPerLine',frmActivePixels,...
      'ActiveVideoLines',frmActiveLines);
  
[frmOutput,frmValid] = pix2frm(edgeOut,ctrlOut);
if frmValid
    figure
    imshow(frmOutput)
    title 'Output Image'
end

Algorithms

This object implements the algorithms described on the Edge Detector block reference page.

See Also

| | (Image Processing Toolbox)

Topics

Introduced in R2015a

Vision HDL Toolbox Documentation

Support