Image Threshold

This function block applies thresholding techniques to images, allowing for the conversion of grayscale images into binary images based on specific criteria. It provides various thresholding methods and adjustable thresholds.

πŸ“₯ Inputs

Image Any The input grayscale or colored image that you would like to apply the thresholding to.

πŸ“€ Outputs

Image Gray The output will be a grayscale image resulting from the applied thresholding.

πŸ•ΉοΈ Controls

Threshold Type A dropdown menu allowing you to select the desired thresholding method (e.g., binary, binary inverse, etc.).

Threshold [Min, Max] A slider that lets you set the minimum and maximum threshold values to be applied to the image. This slider adjusts based on the selected threshold type.

🎨 Features

Multiple Thresholding Methods Choose from a variety of thresholding techniques including binary and truncation methods, giving users flexibility in their image processing.

Dynamic Control The interface reacts according to the threshold type selected, showing or hiding the slider for adjustable thresholds based on the method used.

πŸ“ Usage Instructions

  1. Connect Input Image: Link any image that you wish to threshold to the input.

  2. Select Threshold Type: Choose your desired thresholding method from the Threshold Type dropdown.

  3. Adjust Threshold Range: Use the Threshold [Min, Max] slider to set the minimum and maximum threshold values (if applicable).

  4. Evaluate: Run the block to apply the selected thresholding method, and it will output the processed image.

πŸ“Š Evaluation

When executed, this block processes the input image and outputs a new image that represents the result of the applied thresholding method.

πŸ’‘ Tips and Tricks

Improving Object Detection

For better separation, consider adjusting the threshold values to suit the lighting conditions of your images. Often, a lower minimum threshold helps in retaining more details.

Experiment with Different Threshold Types

Different images may require different thresholding methods. Experiment with THRESH_BINARY, THRESH_BINARY_INV, and THRESH_TRUNC to find the one that best suits your specific image.

Using Otsu's Method

Using the THRESH_OTSU methods will automatically determine the optimal threshold value based on the image histogram, which can be useful for varying lighting conditions.

πŸ› οΈ Troubleshooting

Output Image is Blank

Ensure the input image is correctly connected and that its format is compatible. Also, validate that the threshold values are set correctly within the range of pixel values.

Unexpected Results

If the output does not appear as expected, revisit the selected threshold type and make sure you adjust the slider correctly. Some methods require specific settings to function correctly.

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