With the rapid advancement of digital identity and intelligent authentication technologies, the field of document security is undergoing significant changes. From traditional holography to micro-nano optics and AI-assisted authentication, the industry continues to pursue safer, smarter, and more reliable solutions.
At the SDS2026 Forum, Mr. Hu Zuyuan, the chairman of Image Technology, was invited to give a keynote speech. The speech called “Beyond Holography: Integrating Optics and Artificial Intelligence to Drive the Future of Secure Identification of Identity Documents.”
In his speech, he shared insights on the evolution of optical security technology and discussed how artificial intelligence can reshape the future of secure identity authentication.
Now let’s take a look at his speech and learn more about the presentation
Do you know what a “hologram” is?
When people talk about anti-counterfeiting, they often think of holograms first. So what is holography exactly? How did it become the security technology system we have today?
Hologram is a compound word derived from the Greek: holos (all)+gramma (information). Holography is a way to record and reproduce all the information of an object.
Since the middle and late 20th century, holographic technology has been used more and more in security identification. This includes things like ID and documents, currency and banknotes, and commercial brands. It has become one of the widely used optical anti-counterfeiting technologies in the world.
With years of development, holographic anti-counterfeiting has combined micro-nano manufacturing, materials science, and optical engineering technologies. It has become a mature optical anti-counterfeiting technology system.
The hologram is expressed as a micro-nano structure. The arrangement of these micro-nano structures produces the diffraction color of light.
Of Course, these micro-nano structure colors can also be made using other methods, such as semiconductor lithography technology or plasma processing technology.
In fact, holography has more and more extensive uses, such as holographic optical components, lenses, holographic storage, holographic interferometry, etc.
Five Key Elements of Optical Security Applications
Over the years, applications involving optical security identification of ID documents, vehicle identification, tax stamps, and packaging labels have always been upgraded around five core dimensions:
- (O) Optics
- (C) Colors
- (M) Materials
- (F) Finishing
- (F) Pattern
From early single laser patterns, it has gradually evolved to incorporate a variety of visual effects, such as color-shifting, 3D images, dynamic effects, micro-graphics, and hidden features.
Then what kind of industry technological innovation will emerge when optical anti-counterfeiting technology meets AI (Artificial Intelligence)?
The first AI optical anti-counterfeiting idea
Traditional optical anti-counterfeiting requires manual presetting of parameters such as light angle tolerance values and color tolerances.
AI can establish a machine learning model to learn the diffraction pattern of micro-nano structured colors under specific illumination, analyze the time-series characteristics of dynamic light changes, and automatically adjust the model weights with the data, no longer relying on human experience to judge boundaries.
Second AI optical anti-counterfeiting ideas
What the naked eye can see are surface effects such as color changes and holographic patterns, but AI can dig deep into the invisible data at the bottom of the pattern.
They can extract abstract features from the original pixels that the human eye cannot define at all, such as the local frequency distribution of the holographic pattern and the Fourier phase spectrum of the nano texture.
The third AI optical anti-counterfeiting idea
AI introduces incremental learning and active learning mechanisms, without having to completely retrain the entire system. When the AI detects highly imitative holographic labels that are not covered by the training set, the system will automatically collect the data, start the active learning process, and the model continues to self-upgrade.
Combined with data-enhanced training, the system can stably identify under different lighting, angles, occlusion, or other complex scenes.
More critical is to support distributed updates on the user side, which can not only deal with new counterfeiting technologies, but also avoid revealing data privacy.
When optical anti-counterfeiting meets AI (artificial intelligence), optical anti-counterfeiting technology has a “smart brain”, which can better solve some of the current problems of optical anti-counterfeiting.
In the future, optical anti-counterfeiting technology will continue to be iteratively upgraded. Continuous innovation in materials, colors, patterns, and structures.
New materials that are tougher and more durable, transparent and saturated color effects, and complex three-dimensional dynamic graphics make micro-nano structured color vision products both safe and beautiful.
At the same time, the application scenarios of optical anti-counterfeiting technology will continue to expand, from anti-counterfeiting to social applications. Such as
- High-end packaging and decoration materials
- Visual art and collectibles
- Trend consumer goods and cultural and creative products
- Consumer electronics and 3C products
- Automotive interior and exterior trim
- Architecture and home decoration
After 40 years of deep cultivation and iteration, global optical anti-counterfeiting has completed a qualitative change from “laser holographic anti-counterfeiting” to “optical anti-counterfeiting.”
In the future, with the empowerment of AI (artificial intelligence), it will undergo bigger and further changes, opening up a new intelligent track and taking root in all walks of life with a new attitude.
