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Grayscale Dilation

Morphological dilation of grayscale pixel data

  • Grayscale Dilation block

Vision HDL Toolbox / Morphological Operations


The Grayscale Dilation block performs morphological dilation on a stream of pixel intensity values. You can specify a neighborhood or structuring element of up to 32-by-32 pixels. For line, square, or rectangle structuring elements more than 8 pixels wide, the block uses the Van Herk algorithm to find the maximum pixel value. This algorithm uses only three comparators to find the maximums of all the rows, and then uses a comparison tree to find the maximum pixel value of the row results.

For structuring elements less than 8 pixels wide, or that contain zero elements, the block implements a pipelined comparison tree for each row of the neighborhood. An additional comparison tree finds the maximum pixel value of the row results. If the structuring element contains zeros that exclude pixels, the algorithm saves hardware resources by not implementing comparators for those pixel locations.


This block uses a streaming pixel interface with a pixelcontrol bus for frame control signals. This interface enables the block to operate independently of image size and format. All Vision HDL Toolbox™ blocks use the same streaming interface. The block accepts and returns a scalar pixel value and a bus that contains five control signals. The control signals indicate the validity of each pixel and its location in the frame. To convert a frame (pixel matrix) into a serial pixel stream and control signals, use the Frame To Pixels block. For a full description of the interface, see Streaming Pixel Interface.


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Single image pixel in a pixel stream, specified as an unsigned integer scalar that represents grayscale intensity.

The software supports double and single data types for simulation, but not for HDL code generation.

Data Types: uint8 | uint16 | uint32 | uint64 | double | single | fi(0,N,0)

The pixelcontrol bus contains five signals. The signals describe the validity of the pixel and its location in the frame. For more information, see Pixel Control Bus.

Data Types: bus


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Single output pixel transformed by a morphological operation, returned as a scalar value.

The data type of this output pixel is the same as the data type of the input pixel.

The pixelcontrol bus contains five signals. The signals describe the validity of the pixel and its location in the frame. For more information, see Pixel Control Bus.

Data Types: bus


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

The block supports flat neighborhoods of up to 32-by-32 pixels. To use a structuring element, set the Neighborhood parameter to getnhood (Image Processing Toolbox)(strel (Image Processing Toolbox)(shape)), where shape is specified by the input arguments to the strel (Image Processing Toolbox) function. The minimum neighborhood size is a 2-by-2 matrix, or a 2-by-1 column vector. If the neighborhood is a row vector, it must be at least 8 columns wide and contain no zeros.

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 block allocates (n – 1)-by-Line buffer size memory locations to store the pixels, where n is the number of lines in the Neighborhood parameter value.


  • When you use a block with an internal line buffer inside an Enabled Subsystem (Simulink), the enable signal pattern must maintain the timing of the pixel stream, including the minimum blanking intervals. If the enable pattern corrupts the timing of the pixel stream, you might see partial output frames, corrupted pixel stream control signals, or mismatches between Simulink® and HDL simulation results. You may need to extend the blanking intervals to accommodate for cycles when the enable is low. For more information, see Configure Blanking Intervals.


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The block pads the image with zeros for the dilation operation. For more information, see Edge Padding.

Extended Capabilities

Version History

Introduced in R2016a

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See Also

(Computer Vision Toolbox) | | |