Blob Detector

This function block is designed to identify and analyze blobs within an image. Users can adjust various parameters using sliders to optimize blob detection according to their needs.

📥 Inputs

Image Any Accepts any image data for blob detection.

📤 Outputs

Image Any The output displays the original image with detected blobs highlighted.

Number of Blobs This output indicates the total number of blobs detected in the input image.

Blobs Positions Provides the coordinates of the detected blobs.

Blobs Sizes Supplies the sizes of the detected blobs.

🕹️ Controls

Threshold Range Two sliders that define the minimum and maximum threshold values for blob detection.

Area Range % Two sliders that set the minimum and maximum area of the blobs as a percentage of the image size.

Circularity Range Two sliders that specify the minimum and maximum circularity of the detected blobs.

Convexity Range Two sliders that outline the minimum and maximum convexity of the detected blobs.

Inertia Range Two sliders that allow users to set the minimum and maximum inertia ratio of the detected blobs.

🎨 Features

Customizable Detection Parameters The block allows for fine-tuning of detection parameters, enabling better accuracy for different types of blobs.

Visual Feedback Detected blobs are highlighted on the output image, providing immediate visual confirmation of results.

📝 Usage Instructions

1. Connect Input: Link an image to the Image Any input to be analyzed for blobs.

2. Adjust Parameters: Use the sliders to set the desired detection parameters for thresholds, area, circularity, convexity, and inertia.

3. Run the Block: Evaluate the function block to detect and highlight blobs in the image.

📊 Evaluation

Once executed, this function block processes the input image and outputs a new image with identified blobs along with their corresponding sizes and positions.

💡 Tips and Tricks

Adjusting Sliders

Experiment with the sliders for threshold and area first. Fine-tuning these values helps effectively isolate the desired blobs based on their characteristics.

Refining Results with Filters

After detecting blobs, consider implementing additional filtering measures with Image Threshold or HSV Filter to ensure pristine data for analysis.

Handling Multiple Sizes

If you expect blobs of various sizes, test different configurations for the area range to ensure no significant detections are missed.

🛠️ Troubleshooting

No Blobs Detected

If no blobs are detected, review the input image and the thresholds set for detection. Adjust both the threshold and area sliders to see if better results are achievable.

Visual Overlap of Results

If blobs appear overly clustered or indistinguishable, consider adjusting the Circularity Range and Convexity Range to refine the selections.