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Last updated on: September 18, 2024
As the battle against counterfeit products intensifies, traditional methods of brand protection are falling short, especially in today’s online marketplace. The rise of sophisticated counterfeit tactics demands more advanced solutions to safeguard brands from fakes and scams. Enter image recognition technology, an AI-driven application revolutionizing online brand protection. One of the standout features in this space is the concept of “Fake-known images,” powered by Red Points. This innovative technology leverages machine learning to identify and flag fraudulent, unofficial images frequently used by counterfeiters, providing brands with an automated tool to overcome evolving circumvention techniques.
In this blog, we’ll delve into the role of image recognition in brand protection, explore the concept of “Fake-known images,” and showcase how they can revolutionize your brand’s defense against digital infringements by minimizing manual efforts and scaling impact rapidly.
As counterfeiters and their tactics evolve, traditional text-based methods of detecting counterfeit listings are proving less and less effective. This is where Image Recognition, Image Fingerprinting and Fake-known Images, Optical Character Recognition (OCR), and Logo Recognition come into play.
Image Recognition technology allows systems to identify products within images based on visual characteristics. This makes it harder for counterfeiters to slip through the cracks because, unlike text-based methods, image recognition doesn’t rely on descriptions or keywords. Instead, it scans and matches images, leading to a more accurate detection process.
The same Image Fingerprinting technology that protects copyrighted images —along with favicons to help identify fraudulent websites—is adapted to go a step further and detect “Fake-known images” used by scammers. It creates a unique “fingerprint” for each fraudulent image, allowing the system to identify copies or derivatives of that image across different platforms. This technology excels at tracking down images that have been altered to avoid detection, such as those that are blurred, cropped, recolored, or partially edited. Recognizing shapes, forms, and colors through a continuously learning AI-driven process enables brands to detect their products within images, even when scammers try to obscure or remove branding elements.
OCR is another key player in identifying fake or fraudulent images. This technology extracts text from images to ensure that even the smallest details don’t go unnoticed. It helps identify infringements that might be hidden in logos, product labels, or other visual content containing text. OCR helps uncover contact details, brand misspellings, and name variations to gather seller data and analyze infringement trends too.
Finally, Logo Recognition is crucial for brands frequently targeted by counterfeiters, such as luxury fashion labels. This technology can detect a brand’s logo in images, even if it has been altered or edited, and accurately identify it in any color, size, or version. Extracting and analyzing logos from images can detect fraudulent use and help protect a brand’s identity by catching subtle changes that might not be easily noticeable to the human eye.
“Fake-known images” is an innovative AI feature within Red Points’ Brand Protection Solution. This feature uses machine learning to pick up on images that counterfeiters frequently use to promote and sell fake products. But how does it work?
Fake-Known Image Suggestions use machine learning to identify and recommend images frequently used by counterfeiters. When an image is flagged as associated with fake products, the Red Points system learns to recognize it as a “fake-known image.”
Fake-Known Image Matching, on the other hand, involves a broader image pattern matching of identified fake-known images to those extracted from links, allowing for the detection of counterfeit listings.
Fake-known Image technology significantly speeds up the validation process and accelerates case management when applying automation rules.
Together, Image Recognition, Image Fingerprinting, Fake-known Images, Logo Recognition, and OCR technologies are powerful defenses against counterfeiters’ evolving sophistication in this new fake era. However, what truly sets Red Points apart is how these technologies are integrated and improved using AI and machine learning.
When a counterfeit listing is detected using a “fake-known image,” the system immediately flags it for enforcement, minimizing the need for manual review. This automation not only speeds up the detection process but also ensures that no infringing listings go unnoticed.
In 2023, Red Points processed over 272 million images, extracted more than 10 million logos, matched 131 million images with products, and removed three official images per second, demonstrating the extensive application of our Image Recognition technologies. This proactive approach prevented a backlog of confused buyer complaints from overwhelming customer service. Our AI technology excels at identifying infringements that might easily go unnoticed with manual processes or broad keyword searches, ensuring comprehensive protection against sophisticated counterfeiting tactics.
Integrating AI-driven features like “Fake-known images” into brand protection strategies offers significant benefits. First and foremost is the reduction of manual intervention. Manual processes are costly—if not unpredictable—and drastically limit the impact of brand protection efforts, increasing the cost of inaction. This is particularly evident when managing large volumes of infringements and can lead to overlooking emerging problems and trends across the brand’s portfolio, regions, and platforms. Additionally, manual processing lacks the representative, granular insights needed to drive an informed strategy. In contrast, AI exponentially scales brand protection efforts, providing precise, end-to-end solutions.
Furthermore, AI greatly accelerates detection speed. In a world where counterfeiters can upload fake listings in seconds, this speed is essential. AI-driven tools work around the clock, scanning millions of images in real-time to spot violations, ensuring that your brand protection efforts are always active—even outside regular office hours.
AI-driven tools work around the clock, scanning millions of images in real-time to identify violations, ensuring your brand protection efforts are always active—even outside regular office hours.
While AI offers scalability, the combination of scalability and accuracy truly sets effective brand protection apart. Our AI models, trained on a vast dataset of over 2.7 billion links every month, leverage the most extensive brand protection data ever gathered. In a landscape where the reliability of AI is defined by the quality and depth of its data, our strength lies in the unparalleled precision of our results, providing precise, end-to-end solutions to keep your brand secure.
As counterfeiters continue to evolve, so must the strategies brands use to combat them. “Fake-known images” and other image technologies are already reshaping the landscape of brand protection. These tools provide AI-driven solutions that quickly adapt to the ever-changing risks of online counterfeiting.
For brands looking to stay ahead of the curve, leveraging advanced technologies like Red Points’ Brand Protection Software is not just an option—it’s a necessity. By integrating these tools into your brand protection strategy, you can safeguard your reputation, revenue, and future growth. Failing to do so can expose your reputation, operational efficiency, revenue, and future growth to significant risks posed by counterfeiters.
Ready to see how Red Points’ innovative “Fake-known images” can protect your brand? Request a demo from Red Points today to discover the power of AI-driven brand protection.
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