Harris Corner Filter

This function block detects corner points in images and visualizes them. It is useful for finding feature points for inspection, alignment checks, and shape analysis.

📥 Inputs

• Image Any Input image. Accepts grayscale or color images.

📤 Outputs

• Image Any Annotated image with detected corners marked.

• Corner Size Number of detected corners (numeric).

• Corner Positions List of corner coordinates (multiple points).

🕹️ Controls

• Pixel Threshold Slider to set the minimum corner response needed to consider a pixel as a corner. Higher values reduce detections.

• Block Size Slider controlling the local neighborhood used when evaluating corner strength. Larger values look at wider neighborhoods.

• Aperture Size Slider that adjusts the sampling aperture used for derivative estimation. Useful to tune detection for small or large features.

• Harris Free Parameter Slider to fine-tune the sensitivity of the corner response calculation (expressed as a scaled slider value).

🎨 Features

• Visual output with detected corners overlaid for quick verification.

• Returns both the count and exact positions of detected corners for downstream processing.

• Works with both color and grayscale images; color inputs are handled automatically.

• Adjustable parameters let you trade off sensitivity vs. robustness to noise.

⚙️ How it runs

When active, the block inspects the supplied image, evaluates local corner strength across the image, and marks locations that exceed the chosen threshold. The annotated image, the number of detected corners, and their coordinates are provided as outputs so you can visualize results and feed coordinates into other blocks.

📝 Usage

1. Feed an image into Image Any.

2. Adjust Pixel Threshold to control how many points are reported. Start with a mid value and move up to reduce detections or down to increase them.

3. Tune Block Size and Aperture Size to match the expected feature scale in your image (small features → smaller values; large features → larger values).

4. Use Harris Free Parameter for fine sensitivity adjustments.

5. Use the annotated Image Any output to confirm detections visually.

💡 Tips and Tricks

• Preprocessing: Clean up noise before detecting corners by using Blur or Denoising to reduce false positives.

• Binary conversion: If your features are high-contrast, try Image Threshold first to simplify the image.

• Focus area: Use Image ROI Select or Get ROI to analyze only a specific region and avoid irrelevant corners.

• Post-filtering: Use Find Contour or Approximate Contour to group or simplify detected points into shapes, or use Rectangles in Rectangle to filter corners inside/outside a region.

• Visualization: Preview and inspect results with Show Image. For overlaying markers elsewhere, use Draw Point or Draw Rectangle with the Corner Positions output.

(hint: combining this block with Blur, Image Threshold, Image ROI Select, Find Contour, and Show Image often gives fast, reliable workflows for inspection and measurement tasks.)

🛠️ Troubleshooting

• No corners detected

  • Lower Pixel Threshold or reduce Block Size.

  • Ensure the input has sufficient contrast; consider Image Threshold or Contrast Optimization.

• Too many false corners

  • Increase Pixel Threshold or increase Block Size.

  • Smooth image with Blur or Denoising before detection.

• Detections clustered or noisy

  • Use Find Contour / Approximate Contour to consolidate nearby points into a meaningful shape or to filter by area.

If results look unexpected, preview the annotated Image Any output with Show Image to guide parameter tuning.