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Morphological closing of grayscale pixel data


visionhdl.GrayscaleClosing performs a morphological dilation operation, followed by a morphological erosion operation, using the same neighborhood for both calculations. The object operates on a stream of pixel intensity values. You can specify a neighborhood, or structuring element, of up to 32×32 pixels. For line, square, or rectangle structuring elements more than 8 pixels wide, the object uses the Van Herk algorithm to find the maximum and minimum. For structuring elements less than 8 pixels wide, or that contain zero elements, the object implements a pipelined comparison tree to find the maximum and minimum.

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 full description of the interface, see Streaming Pixel Interface.


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.


C = visionhdl.GrayscaleClosing returns a System object, C, that performs morphological closing on a pixel stream.

C = visionhdl.GrayscaleClosing(Name,Value) returns a System object, C, 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.



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

The object supports neighborhoods of up to 32×32 pixels. To use a structuring element, specify Neighborhood as getnhood (Image Processing Toolbox)(strel (Image Processing Toolbox)(shape)). The minimum neighborhood size is a 2×2 matrix, or a 2×1 column vector. If the neighborhood is a row vector, it must be at least 8 columns wide and contain no zeros.

Default: ones(3,3)


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

Size of 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 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 Neighborhood parameter value.

Default: 2048


stepReport closed pixel value based on neighborhood
Common to All System Objects

Allow System object property value changes


collapse all

Perform morphological closing on a grayscale thumbnail image.

Load a source image from a file. Select a portion of the image matching the desired test size.

frmOrig = imread('rice.png');
frmActivePixels = 64;
frmActiveLines = 48;
frmInput = frmOrig(1:frmActiveLines,1:frmActivePixels);
title 'Input Image'

Figure contains an axes. The axes with title Input Image contains an object of type image.

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

frm2pix = visionhdl.FrameToPixels(...

Create a filter object.

mclose = visionhdl.GrayscaleClosing( ...

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

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);

Prepare to process pixels by preallocating output vectors.

[~,~,numPixelsPerFrame] = getparamfromfrm2pix(frm2pix);
pixOut = uint8(zeros(numPixelsPerFrame,1));
ctrlOut = repmat(pixelcontrolstruct,numPixelsPerFrame,1);

For each pixel in the padded frame, compute the morphed value. Monitor the control signals to determine the 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;
    [pixOut(p),ctrlOut(p)] = mclose(pixIn(p),ctrlIn(p));
    if (ctrlOut(p).valid && foundValOut==0)
        foundValOut = p;
sprintf('object latency is %d cycles',foundValOut-foundValIn)
ans = 
'object latency is 384 cycles'

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

pix2frm = visionhdl.PixelsToFrame(...
[frmOutput,frmValid] = pix2frm(pixOut,ctrlOut);
if frmValid
    imshow(frmOutput, 'InitialMagnification',300)
    title 'Output Image'

Figure contains an axes. The axes with title Output Image contains an object of type image.


This object implements the algorithms described on the Grayscale Closing block reference page.

Introduced in R2016a