> For the complete documentation index, see [llms.txt](https://docs.augelab.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.augelab.com/function-blocks/blocks-reference/detections-shapes/detectors/blob-detector.md).

# Blob Detector

This function block detects blob-like features (bright/dark roundish objects) in an image. Use the sliders to tune detection sensitivity and shape filters so the block finds only the blobs you care about.

## 📥 Inputs <a href="#inputs" id="inputs"></a>

`Image Any` Image to analyze for blobs.

## 📤 Outputs <a href="#outputs" id="outputs"></a>

`Image Any` Visual result image with detected blobs marked.\
`Number of Blobs` Count of detected blobs.\
`Blobs Positions` List of blob center positions (x, y).\
`Blobs Sizes` Sizes (diameter) of detected blobs.

## 🕹️ Controls <a href="#controls" id="controls"></a>

`Threshold Range` Minimum and maximum intensity thresholds used to detect candidate blobs.\
`Area Range` Minimum and maximum blob area as a percentage of the image scale.\
`Circularity Range` Allowed circularity range to favor round shapes.\
`Convexity Range` Allowed convexity range to exclude highly concave shapes.\
`Inertia Range` Allowed inertia ratio range to filter elongated vs. round blobs.

## 🎯 Features <a href="#features" id="features"></a>

* Visual feedback: detected blobs are drawn on the output image so you can inspect results immediately.
* Shape filtering: narrow detections using area, circularity, convexity and inertia sliders to reduce false positives.
* Live tuning: slider adjustments take effect on the next evaluation so you can iterate quickly.

## 📝 Usage Instructions <a href="#usage" id="usage"></a>

1. Provide an image to `Image Any`.
2. Start with a broad `Threshold Range` and adjust until most blob candidates appear on the output image.
3. Use `Area Range` to remove very small or very large detections relative to your object size.
4. Tune `Circularity Range`, `Convexity Range` and `Inertia Range` to exclude shapes that are not blob-like.
5. Inspect results in the output image and read the numeric outputs for automation or logging.

## 📊 Evaluation <a href="#evaluation" id="evaluation"></a>

When run, the block analyzes the input image and returns a marked image plus the number, positions and sizes of detected blobs. Use these outputs downstream for measurement, counting or decision logic.

## 💡 Tips and Tricks <a href="#tips-and-tricks" id="tips-and-tricks"></a>

* Preprocess noisy images with `Blur` or `Denoising` to reduce spurious small detections.
* Convert complex scenes to a clearer foreground with `Image Threshold` or `HSV Filter` before feeding this block.
* If you only need to analyze a region, crop first using `Image ROI Select` to speed up detection and avoid background blobs.
* For large images, try `Image Resizer` to lower resolution and increase processing speed while keeping meaningful blob sizes.
* Visualize or save results using `Show Image` and `Image Logger` when tuning or to keep records.
* Combine with drawing blocks such as `Draw Detections` to overlay counts or rectangular markers on the image for operator displays.

(hint: use these related blocks to improve robustness and speed: `Blur`, `Image Threshold`, `Image ROI Select`, `Image Resizer`, `Denoising`, `Show Image`, `Image Logger`, `Draw Detections`)

## 🛠️ Troubleshooting <a href="#troubleshooting" id="troubleshooting"></a>

* No blobs detected: widen the `Threshold Range` and increase the `Area Range`; check the input image contrast.
* Too many small false blobs: increase the minimum in `Area Range` or apply `Blur` / `Image Threshold` to remove noise.
* Detecting elongated or irregular shapes: tighten `Circularity Range` and/or adjust `Inertia Range` to favor round blobs.
* Inconsistent detections across frames: use consistent lighting, or apply preprocessing (`Auto Contrast` / `Denoising`) to stabilize input images.