Subtract Images

This function block computes the pixel-wise difference between two images to highlight changes or defects. It is useful for comparison tasks such as detecting deviations from a reference, visual inspection, and motion/change analysis.

📥 Inputs

Actual Image Input socket — the image to be compared (source image).

Reference Image Input socket — the image to subtract from the actual image (baseline or reference).

📤 Outputs

Difference Image Output socket — resulting image showing the per-pixel difference between the inputs.

🕹️ Controls

This block has no user-facing controls or widgets.

🎨 Features

• Produces a visual difference image that emphasizes pixel-level changes between two equally sized images.

• Works with color or grayscale images (both inputs must share the same dimensions).

• Simple and fast operation suitable as a preprocessing step for downstream detection or logging.

⚙️ Running Mechanism

When both input sockets provide images, the block produces a Difference Image by performing a per-pixel subtraction of the reference from the actual image. The block requires that both images have identical dimensions; if sizes differ, the block will report an error. The difference output can be fed into visualization, thresholding or counting blocks to interpret the result.

📝 Usage

1. Connect a source image to the Actual Image input socket.

2. Connect a baseline or reference image to the Reference Image input socket.

3. Make sure both images have the same size. If not, insert the Image Resize block before this block.

4. Use the Difference Image output for visualization or further processing.

Examples of common workflows:

• Visual inspection: connect Difference Image to Show Image to preview changes.

• Binary detection: feed Difference Image into Image Threshold to create a mask of changed areas.

• Quantification: pass the thresholded mask to Non-zero of Image to count changed pixels.

• Logging: save results with Image Logger or Image Write for record keeping.

💡 Tips and Tricks

• Ensure image alignment and resolution match before subtraction. Use Image Resize or geometric alignment blocks if needed.

• To make subtle differences more visible, apply Contrast Optimization or Normalize Image to the Difference Image before visualization.

• Convert the difference to a binary mask using Image Threshold to isolate meaningful changes. Combine the mask with Non-zero of Image to get a numeric measure of change.

• For quick inspection during development, connect the output to Show Image. For automated runs, save results with Image Logger or Image Write.

• If you expect single-channel output, check input channel formats (grayscale vs RGB) upstream and convert consistently.

🛠️ Troubleshooting

• Mismatched image sizes Ensure both inputs share the same width and height. Use the Image Resize block to resample one of the images.

• Very low or no visible difference Apply Contrast Optimization or Normalize Image to amplify small changes, or use Image Threshold to create a binary mask.

• Unexpected colors or channels Confirm both inputs are in the same color space (both grayscale or both RGB) before connecting them.

• Need a numeric change measure After thresholding the difference, send the mask to Non-zero of Image to obtain a count of changed pixels.