Republishing photos from other websites is a signal of low quality to Google algorithms. In the post HCU age, Google rewards unique, individualized content from real people with real names. It’s an important metric to differentiate quality from noise.
For instance, when I first published the previous blog post to my site, I was in a big hurry and I compromised by sharing an AI created image. It was clearly not unique or created by humans. I forgot to replace the image with a unique self-taken photo, and it cost me.
Lesson learned.
But how do they know if an image is unique content?
Google evaluates whether an image is unique using a combination of visual analysis, metadata comparison, and contextual relevance. Here’s a breakdown of how it works:
1. Visual Fingerprinting / Perceptual Hashing
Google uses algorithms that create a “fingerprint” of an image based on its visual features (shapes, colors, patterns, textures). Even if the image is resized, cropped, or slightly altered, the core features can often still be recognized.
Example: You upload a photo of a sunset. Google compares its visual fingerprint to millions of others it has indexed to see if it already exists or is closely similar.
2. EXIF and Metadata
Images contain embedded metadata (EXIF data), which includes:
- Camera make/model
- Timestamps
- GPS location
- Editing software used
If multiple images share identical metadata or lack it entirely (common with stock photos), this could signal that the image isn’t unique.
3. File-Level Similarity
Google checks:
- Image dimensions
- File size
- Compression artifacts
- File names and alt text (especially for SEO)
4. Contextual Usage
If the same image appears on many different sites, especially in similar contexts or surrounded by identical text, it’s flagged as duplicate or non-unique.
Even if you’ve uploaded a stock image with a unique filename, Google may see that it’s widely used and treat it as non-original.
5. Reverse Image Search Matching
Google essentially performs the same action a user would if they used Google Reverse Image Search — it checks where else the image (or close variants) exists online.
6. AI and Pattern Recognition
Google’s AI systems can now detect manipulations, AI-generated images, and composite works (e.g., stock photo backgrounds with custom overlays).
5 Ways To Increase Image Uniqueness:
- Use original photography or custom illustrations
- Avoid common stock photos (or significantly modify them)
- Include unique elements (e.g., logo overlays, branded filters)
- Add original alt text and captions
- Change file names to describe the unique content
