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visionhdl.Opening

Morphologically open binary pixel stream

Description

The visionhdl.Opening System object™ morphologically opens a binary pixel stream. This operation morphologically erodes and then morphologically dilates each pixel by using the same neighborhood for both calculations. The object operates on a stream of binary intensity values.

To morphologically open a binary pixel stream:

  1. Create the visionhdl.Opening object and set its properties.

  2. Call the object with arguments, as if it were a function.

To learn more about how System objects work, see What Are System Objects?

Creation

Description

opener = visionhdl.Opening creates a System object that morphologically opens a binary pixel stream.

example

opener = visionhdl.Opening(Name,Value) sets properties using one or more name-value arguments. For example, 'Neighborhood',getnhood(strel('disk',4)) specifies a 4-by-4 disk-pattern neighborhood.

Properties

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Unless otherwise indicated, properties are nontunable, which means you cannot change their values after calling the object. Objects lock when you call them, and the release function unlocks them.

If a property is tunable, you can change its value at any time.

For more information on changing property values, see System Design in MATLAB Using System Objects.

Pixel neighborhood, specified as a vector or matrix of binary values.

The object supports neighborhoods of up to 32-by-32 pixels. To use a structuring element, set the Neighborhood property to getnhood(strel(shape)), where shape is specified by the input arguments to the strel (Image Processing Toolbox) function.

Size of the line memory buffer, specified as a positive integer. 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 buffer 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 Neighborhood property value.

Method for padding the boundary of the input image, specified as one of these values.

  • 'Constant' — The object pads the image with ones for the erosion operation and with zeros for the dilation operation. These values prevent opening 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 that are used by the object and reduces the blanking that is required between frames. However, this option 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. To avoid using pixels calculated from undefined padding values, mask off the n/2 pixels around the edge of the frame for downstream operations. n is the size of the operation kernel. For more details, see Increase Throughput by Omitting Padding.

For more information about these methods, see Edge Padding.

Usage

Description

example

[pixelout,ctrlout] = opener(pixelin,ctrlin) returns the next binary pixel value, pixelout, resulting from morphologically opening the neighborhood around each input binary pixel, pixelin.

This object uses a streaming pixel interface with a structure for frame control signals. This interface enables the object to operate independently of image size and format and to connect with other Vision HDL Toolbox™ objects. The object accepts and returns a scalar pixel value and control signals as a structure containing five signals. The control signals indicate the validity of each pixel and its location in the frame. To convert a pixel matrix into a pixel stream and control signals, use the visionhdl.FrameToPixels object. For a description of the interface, see Streaming Pixel Interface.

Input Arguments

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Input pixel, specified as a logical value of 0(false) or 1 (true).

You can simulate System objects with a multipixel streaming interface, but you cannot generate HDL code for System objects that use multipixel streams. To generate HDL code for multipixel algorithms, use the equivalent Simulink® blocks.

Data Types: logical

Control signals accompanying the input pixel stream, specified as a pixelcontrol structure containing five logical data type signals. The signals describe the validity of the pixel and its location in the frame. For more details, see Pixel Control Structure.

Data Types: struct

Output Arguments

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Output pixel that is transformed by a morphological operation, returned as a logical value.

Data Types: logical

Control signals accompanying the output pixel stream, returned as a pixelcontrol structure containing five logical data type signals. The signals describe the validity of the pixel and its location in the frame. For more details, see Pixel Control Structure.

Data Types: struct

Object Functions

To use an object function, specify the System object as the first input argument. For example, to release system resources of a System object named obj, use this syntax:

release(obj)

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stepRun System object algorithm
releaseRelease resources and allow changes to System object property values and input characteristics
resetReset internal states of System object

Examples

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Load a source image from a file. Select a portion of the image that matches the desired test size. This source image contains pixel intensity values of uint8 data type. Apply a threshold to convert the pixel data to binary values.

frmOrig = imread('rice.png');
frmActivePixels = 64;
frmActiveLines = 48;
frmInput = frmOrig(1:frmActiveLines,1:frmActivePixels);
frmInput = frmInput>128;
figure
imshow(frmInput,'InitialMagnification',300)
title 'Input Image'

Create a serializer System object™ and define inactive pixel regions. Set the number of inactive pixels following each active line to at least double the horizontal size of the neighborhood. Set the number of lines following each frame to at least double the vertical size of the neighborhood.

frm2pix = visionhdl.FrameToPixels(...
      'NumComponents',1, ...
      'VideoFormat','custom', ...
      'ActivePixelsPerLine',frmActivePixels, ...
      'ActiveVideoLines',frmActiveLines, ...
      'TotalPixelsPerLine',frmActivePixels+20, ...
      'TotalVideoLines',frmActiveLines+10, ...
      'StartingActiveLine',3, ...     
      'FrontPorch',10);

Create a morphological open System object.

 opener = visionhdl.Opening(...
          'Neighborhood',ones(5,5));

Serialize the test image by calling the serializer object. pixin is a vector of intensity values. ctrlin is a vector of control signal structures.

[pixin,ctrlin] = frm2pix(frmInput);

Prepare to process the pixel stream by preallocating output vectors.

[~,~,numPixelsPerFrame] = getparamfromfrm2pix(frm2pix);
pixout = false(numPixelsPerFrame,1);
ctrlout  = repmat(pixelcontrolstruct,numPixelsPerFrame,1);

For each pixel in the padded frame, compute the morphed value. Monitor the control signals to determine latency of the object. The latency of a configuration depends on the number of active pixels in a line and the size of the neighborhood.

foundValIn = false;
foundValOut = false;
for p = 1:numPixelsPerFrame  
    if (ctrlin(p).valid && foundValIn==0)
        foundValIn = p;
    end
    [pixout(p),ctrlout(p)] = opener(pixin(p),ctrlin(p));
    if (ctrlout(p).valid && foundValOut==0)
        foundValOut = p;
    end
end
objLatency_cycles= foundValOut - foundValIn
objLatency_cycles = 368

Create a deserializer System object with a format that matches the serializer format. Convert the pixel stream to an image frame by calling the deserializer object. Display the resulting image.

pix2frm = visionhdl.PixelsToFrame(...
      'NumComponents',1, ...
      'VideoFormat','custom', ...
      'ActivePixelsPerLine',frmActivePixels, ...
      'ActiveVideoLines',frmActiveLines, ...
      'TotalPixelsPerLine',frmActivePixels+20);
[frmOutput,frmValid] = pix2frm(pixout,ctrlout);
if frmValid
    figure
    imshow(frmOutput,'InitialMagnification',300)
    title 'Output Image'
end

Algorithms

This object implements the algorithms described on the Opening block reference page.

Extended Capabilities

Version History

Introduced in R2015a

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See Also

Objects

Blocks

Functions

  • (Image Processing Toolbox)