> 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/line-detector.md).
# Line Detector
This function block detects and highlights straight lines in an input image. It offers simple controls to guide the detection toward a preferred orientation, tune sensitivity, and pick a single "selected" line according to different selection modes. The block also produces a histogram visualization of intensity values along the chosen line to help with further analysis.
## đĨ Inputs
`Image Any` Image to analyze for line structures (color or grayscale).
## đ¤ Outputs
`Lined Image` Image with detected lines visualized.
`Histogram Image` Intensity histogram image with optional overlay showing statistics for the selected line.
`Number of Lines` Count of detected lines after any filtering.
`Selected Line` A single selected line (shape) chosen according to the selected selection mode.
`Lines` All detected lines (shapes), returned as a list when applicable.
## đšī¸ Controls
`Preferred Angle` Choose the orientation (in degrees) you are most interested in (0â180). This biases detection toward lines with that orientation.
`Tolerance (deg)` Set how much deviation from the preferred angle is allowed. Smaller values restrict detection to lines close to the preferred orientation.
`Line Selection` Pick how to choose the single representative line from multiple detections. Options include First Position, Last Position, Longest, Shortest, Middle Position, and Median Length.
`Hough Threshold (Votes)` Adjust sensitivity for line detection. Higher values make detection stricter (fewer lines); lower values detect weaker lines.
`Min. Line Length (pixels)` Ignore very short segments by setting a minimum length for detected lines.
`Max. Line Gap (pixels)` When using segment-based detection, this controls how far apart broken segments may be to still be joined into a single line.
## đ Running mechanism
* The input image is prepared for line analysis (converted and enhanced as needed).
* Prominent edges and segments are located across the image.
* Detected segments are collected and (optionally) filtered to keep those close to the `Preferred Angle` within the `Tolerance (deg)`.
* One line is selected based on the `Line Selection` control.
* The result image is rendered with all found lines shown and the selected line highlighted.
* A histogram image of intensity values is produced; if a line is selected, the histogram will also show basic statistics (mean, optionally standard deviation) for pixels sampled along that line.
## ⨠Features
* Visual output that draws all detected lines and highlights a chosen line for easy inspection.
* Flexible selection modes to choose a single line that best fits your task.
* Angle-based filtering to focus on a desired orientation.
* Simple histogram output tied to the chosen line for quick intensity analysis.
* Adjustable parameters to trade off sensitivity vs noise tolerance.
## đ Usage Instructions
1. Connect an image-producing block to the `Image Any` input (for example, a camera or an image loader).
2. Set `Preferred Angle` to the orientation you expect in the scene.
3. Reduce `Tolerance (deg)` to focus tightly on that orientation, or increase it to accept more varied angles.
4. Tune `Hough Threshold (Votes)`, `Min. Line Length`, and `Max. Line Gap` to find a balance between missing weak lines and including noise.
5. Use `Line Selection` to pick the single line representation that makes sense for your task.
6. Inspect the `Lined Image` and `Histogram Image` outputs; use the line shapes for downstream processing.
## đĄ Tips and Tricks
* For noisy images, add a `Blur` block before this block to smooth noise and improve detection stability.
* If your source images are very large, use `Image Resize` to lower resolution and speed up detection while keeping meaningful structures.
* To focus processing on a particular region, crop first with `Image ROI Select` or `Get ROI` then run this block on the cropped image.
* After detection, combine the `Selected Line` or `Lines` outputs with `Line Geometry` to measure angles, distances, intersections or extract coordinates.
* For visual debugging, feed the `Lined Image` into `Show Image` to view results in a larger viewer, or save examples using `Image Logger` or `Image Write`.
* Use `Histogram On Line` when you need more specialized peak analysis along a single straight scan line; it complements the histogram produced here.
* To draw or annotate specific measurement lines interactively, combine with `Draw Line` and then analyze the drawn line with this block.
(hints above use only blocks from the provided list)
## đ ī¸ Troubleshooting
* No lines detected: Lower `Hough Threshold (Votes)`, decrease `Min. Line Length`, or increase `Tolerance (deg)` so more candidates are accepted.
* Too many spurious lines: Increase the `Hough Threshold (Votes)` or raise `Min. Line Length` to ignore small noisy segments.
* Selected line is unexpected: Try different `Line Selection` modes (e.g., Longest or Middle Position) or adjust the preferred angle and tolerance.
* Histogram seems unrelated to the selected line: Ensure the selected line lies fully inside the image area; crop with `Image ROI Select` if necessary.
If you need more stable results in production, preprocess images (lighting, contrast) and test parameter ranges on representative samples before deploying.