Hough Transform Online Free — Lines & Circles

How the Hough Transform actually finds lines and circles

The Hough Transform works on an edge map, not the raw photo, so it first runs a Canny edge detector to reduce the image to thin contours — the same preprocessing you can preview with our edge detection tool. For line detection it then maps every edge pixel into a parameter space: each pixel votes for all the lines that could pass through it, expressed in polar form (rho, theta) rather than slope-intercept so vertical lines are handled cleanly. Accumulator cells that collect the most votes correspond to real straight lines in the image. The Standard Hough Line Transform returns infinite lines as angle-distance pairs, while the Probabilistic variant (HoughLinesP) samples a random subset of edge points and returns finite segments with start and end coordinates — far faster, and usually what you want for documents, road markings, or measuring skew. Circle detection uses the Hough Gradient method, which votes in a center-plus-radius space and uses the gradient direction at each edge pixel to keep the accumulator tractable.

Choosing the right mode and tuning the parameters

Pick Standard lines when you need precise angles across the whole frame, Probabilistic lines when you want clean segments with control over minimum length and maximum gap, and Circle detection for round objects like coins, pupils, dials, or pipe ends. A few settings carry most of the weight:

• Votes / threshold — raise it to keep only strong, confident lines; lower it to catch faint ones at the cost of false positives.
• Min line length and max gap (probabilistic) — reject short noise segments and bridge dashed or broken edges into single lines.
• Min/max radius and min distance (circles) — constrain the size range and spacing so overlapping or nested circles do not merge.
• Edge sensitivity — if too many or too few shapes appear, the real fix is usually the underlying edge step, which you can refine with threshold segmentation before running the transform.

Where it's used, and why it runs in your browser

The Hough Transform is a workhorse for deskewing scanned documents, detecting lanes and grid lines, measuring angles in engineering drawings, counting circular parts on an assembly line, and locating coins or biological cells. Because it operates on geometry rather than learned features, it is predictable and easy to debug, which pairs well with shape-based pipelines like contour detection for follow-up measurement. Pixlane runs the full OpenCV transform on-device with WebAssembly, so your images are processed entirely in the browser and never uploaded to a server. It is private by default, free, has no watermark or signup, and gives you instant results you can re-tune in real time — adjusting thresholds and watching the detected lines or circles redraw without a round trip to the cloud.