Morphological Transformations

This function block applies morphological transformations to input images, which can help in various image processing tasks by performing operations like erosion and dilation.

📥 Inputs

Image Any This input accepts any image data that you wish to apply morphological transformations to.

📤 Outputs

Image Any This output provides the transformed image after applying the selected morphological operation.

🕹️ Controls

Morph Type A dropdown menu to select the type of morphological operation you wish to apply, such as erosion, dilation, opening, closing, and more.

Morph Shape A dropdown menu to select the geometric shape of the structuring element used in morphological operations, such as rectangular, elliptical, or cross-shaped kernels.

Kernel Size A slider to define the size of the kernel used in the morphological transformations. It determines how much the neighborhood pixels will affect the transformation.

Iterations A slider used when erosion or dilation is selected to determine how many times the operation will be applied.

🎨 Features

Versatile Transformations Offers a variety of operations to manipulate image structures based on their shapes and pixel connectivity.

Dynamic Control Over Parameters Users can adjust kernel size and operation type dynamically, allowing for fine-tuning based on specific requirements.

📝 Usage Instructions

1. Connect Input: Link the input image to the Image Any input.

2. Select Morph Type: Choose the desired morphological operation from the Morph Type dropdown.

3. Choose Morph Shape: Select the shape of the structuring element from the Morph Shape dropdown.

4. Adjust Kernel Size: Use the Kernel Size slider to specify the size of the structuring element.

5. Set Iterations: If the selected operation is erosion or dilation, adjust the Iterations slider to determine how many times to apply the operation.

6. Evaluate: Run the block to apply the specified morphological transformation to the input image.

📊 Evaluation

Upon running, this function block outputs the transformed image based on the selected morphological operation and parameters.

💡 Tips and Tricks

Choosing the Right Operation

If the goal is to remove noise and small objects, use MORPH_OPEN. For filling small holes in objects, use MORPH_CLOSE.

Experimenting with Kernel Shapes

Different shapes can yield different results. Try using MORPH_ELLIPSE for smoother transitions and MORPH_CROSS for more pronounced results, depending on the images being processed.

Combining Operations

Consider chaining multiple morphological operations by using multiple instances of this block to refine your image further.

🛠️ Troubleshooting

No Changes in Output

Ensure that the input image is not empty. Also check if the kernel size is too small—try increasing the kernel size for more noticeable changes.

Errors Applying the Morphological Transformations

If you encounter errors during the evaluation, check to ensure that the input image format is supported and that all parameters are set correctly before attempting to run the block again.