Watermark Detector

Detect visible watermarks in images — stock photo logos, copyright text, and semi-transparent overlays. Analyzes edge patterns, transparency anomalies, and repetition. All processing in your browser.

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How to interpret results

The detector analyzes six signals: center and diagonal edge density (where watermarks are typically placed), semi-transparent overlay patterns, tiled repetition, faint edge density (characteristic of light watermark text), and border region anomalies. A confidence above 60% suggests a watermark is likely present. Results between 35-60% are inconclusive. Detection is heuristic-based — false positives can occur with images containing centered text, logos, or translucent overlays that are part of the original design.

Edge Analysis

Sobel edge detection identifies areas with unusual edge density. Watermark text and logos create distinct edge patterns that differ from natural image content — especially in center and diagonal regions where watermarks are typically placed.

Transparency Detection

Semi-transparent watermarks create blocks of pixels with narrowed color range and elevated brightness — a statistical signature that differs from natural image areas. The detector identifies these blocks and scores them.

Pattern Repetition

Tiled watermarks (repeated across the image) produce periodic autocorrelation peaks in the edge map. The detector scans for these regular intervals, which are absent in natural photographs.

How does watermark detection work?

Visible watermarks leave statistical fingerprints that differ from natural image content. This tool applies Sobel edge detection to build an edge density map, then analyzes six signals: center and diagonal region edge anomalies (where stock agencies place logos), semi-transparent overlay patterns (narrowed color range with elevated brightness), tiled repetition via autocorrelation, faint edge density (characteristic of light text overlays), and border region analysis. These signals are weighted and combined into a confidence score. For deeper forensic analysis of image manipulation, try the ELA Scanner or the Authenticity Checker.

Common watermark types and detection accuracy

Stock photo watermarks (Shutterstock, Getty, Adobe Stock) typically use semi-transparent diagonal text or centered logos — these produce the strongest detection signals. Small corner-only watermarks (copyright stamps, photographer logos) may produce lower confidence scores due to their limited coverage area. Tiled watermarks that repeat across the image are detected via autocorrelation peaks. Detection is heuristic-based and may produce false positives on images with centered text, UI overlays, or translucent design elements. For analyzing text content within images, the Text Scanner (OCR) can extract readable text. To compare a watermarked and unwatermarked version, use the Similarity Scanner.

Watermark detection for copyright verification

Content moderators, media buyers, and publishers can use watermark detection to verify that images in their pipeline are properly licensed. If an image intended for publication still contains a stock agency watermark, it likely was not purchased. This tool flags such images before they reach production. For adding your own watermarks to protect your work, the Image Watermark tool supports text and image overlays with adjustable opacity and positioning. To check whether an image has been edited after watermarking, the Forgery Heatmap combines multiple forensic signals.

Privacy and client-side processing

All watermark detection runs entirely in your browser — the image never leaves your device. Edge detection, block analysis, and autocorrelation are performed using the Canvas API and JavaScript. No server processing, no uploads, no data retention. This is particularly important for legal and editorial workflows where image provenance must remain confidential. The same privacy-first architecture powers all 76 Scanly tools, from the EXIF Checker to the Image Encryption tool. Explore the full set at Scanly's toolkit. Learn more in our articles on image watermark guide and detecting edited photos.

Frequently Asked Questions

How do I check if an image has a watermark?

Upload the image and the detector automatically analyzes it for watermark signals — edge density anomalies in center and diagonal regions, semi-transparent overlays, tiled repetition patterns, and faint edge characteristics. Results include a confidence score (0-100%), a verdict, and a detailed breakdown of each signal. Processing happens instantly in your browser.

What types of watermarks can this tool detect?

The tool is most effective at detecting semi-transparent stock photo watermarks (Shutterstock, Getty, Adobe Stock style), centered or diagonal text overlays, tiled repeating patterns, and faint copyright stamps. Small corner-only watermarks may produce lower confidence scores. The tool detects visible watermarks only — it does not detect invisible/steganographic watermarks embedded in pixel data.

Can this tool remove watermarks from images?

No. This tool only detects whether a watermark is present — it does not remove, erase, or alter the image in any way. Watermark removal from copyrighted images may violate intellectual property laws. If you need to add your own watermark for copyright protection, use the Image Watermark tool available on Scanly.

Why does the detector show false positives?

False positives can occur with images containing centered text, UI overlays, translucent design elements, lens flare, or intentional graphic overlays that mimic watermark characteristics. The detector uses heuristic analysis, not machine learning, so it identifies statistical patterns similar to watermarks rather than recognizing specific logos. Scores between 35-60% should be treated as inconclusive.

What does the edge density heatmap show?

The heatmap overlays color on regions with elevated edge density — brighter red areas indicate higher edge activity. Watermark text and logos create concentrated edge patterns that stand out against natural image content. Areas highlighted in the center or diagonal regions are particularly significant, as stock agencies typically place watermarks in these positions.

Does this tool upload my image to a server?

No. All watermark detection analysis — edge detection, block analysis, transparency scoring, and autocorrelation — runs entirely in your browser using the Canvas API and JavaScript. Your image never leaves your device. There are no server uploads, no data retention, and no network requests during analysis.