[IPHINT Editor’s Note]

Many creators today say that "failing to detect" image theft is their biggest challenge.

To solve this, IPHINT is developing technology that tracks stolen images using pattern-based detection rather than simple visual similarity searches.

If you create content, you’ve likely thought this at least once: "There is just too much image theft."

This isn't just a feeling; it’s a problem that is becoming objectively more severe. From social media and online malls to blogs and even advertisements, instances of images being used without credit have become a daily occurrence.

The real issue is that theft has become too "easy."

Images are copied much faster than text, and once they spread, tracking the original source becomes nearly impossible. Simply cropping an image or changing its colors can make the original unrecognizable to standard tools.

Even worse, most creators "don't even know they've been stolen from." In many cases, there is no way to verify where or how their images are being used.

Search engines have their limits, and manual tracking is practically impossible in terms of time and effort. Meanwhile, the damage continues to mount—brand images are tarnished, the value of creative work declines, and in some cases, revenue is directly impacted.

Despite this, many people still think: "Isn't this just inevitable?"

However, the situation is changing. As technology advances, new methods are emerging that analyze and track the "patterns" of an image, going far beyond basic similarity searches. Now, only one thing matters: image theft is no longer an unstoppable problem—it’s a matter of "whether you can detect it."

And that shift is beginning right now.

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