TECNO Upgrades Universal Tone with Expanded Skin Tone Color Card Making It More Inclusive

Marco Lancaster

February 20, 2025

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TECNO continues to build its reputation as an AI-driven tech brand. Known as one of the top names in the mid-range smartphone market in recent years, the company has been making big improvements to bring flagship-like camera features. With its new AI technology, TECNO is advancing multi-skin tone imaging by making major updates to its Universal Tone technology.

The update brings a better multi-skin tone color card with 372 patches and upgrades to the Multi-Skin Tone Color Restoration Engine, greatly improving skin tone accuracy. These changes ensure more precise and inclusive skin tone representation across different ethnicities and lighting situations in mobile photography.

Tecno Universal Tone Technology Gets Massive Improvements

This advanced technology will debut in the upcoming TECNO CAMON 40 Series, launching at MWC Barcelona 2025 in March. Visitors can experience it firsthand at TECNO’s booth: Hall 6, Stand 6B11, Fira Gran Via.

Expanding the Skin Tone Database for True-to-Life Representation

TECNO has improved its Universal Tone multi-skin tone color card, now with 372 color patches. The goal is to deliver a more complete and inclusive database. This update makes sure that skin tones are shown accurately for users in Southeast Asia, South Asia, Africa, the Middle East, and Eastern Europe. The bigger color card helps both the science and practical use of skin tone measurements, acting as an important tool for TECNO’s Universal Tone algorithms. With this better set of data, Universal Tone can now capture and show a wider range of skin tones more accurately.

At MWC 2025, TECNO will show two versions of the updated color card—one for darker skin tones and another for lighter skin tones, covering the full range of tones.

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Going even further, TECNO creates a special color card for Saudi Arabia, with 186 Saudi skin tone patches. It has been working with the University of Leeds (UK) and Dar Al-Hekma University (Saudi Arabia) since late 2024. This shows TECNO’s focus on accurate and inclusive skin tone representation. It works to make sure Saudi skin tone capture is accurate. TECNO will keep improving Universal Tone with research on local skin tones, lighting, and real-life situations, making sure it works well for users in different regions.

Read Also: HONOR ALPHA Plan: A Bold New Vision to be Unveiled at MWC 2025

Enhancing the Multi-Skin Tone Color Restoration Engine for Unmatched Precision and Accuracy

The Multi-Skin Tone Color Restoration Engine is a key part of Tecno Universal Tone Tech. It has been improved with the updated CCM Skin Tone Calibration Algorithm. It is also getting a new Spectrum-Based Automatic White Balance (AWB) Algorithm. The CCM algorithm, trained with TECNO’s new color card, ensures precise color calibration. Meanwhile, the AWB algorithm, based on spectral predictions of skin tones, fixes color shifts in photos. It delivers uniform backgrounds and enhances exposure and white balance for diverse skin tones in the same shot. These combined upgrades result in a 50% improvement in skin tone accuracy. Therefore, it delivers natural, lifelike portraits across a wide range of skin tones and lighting conditions.

Universal Tone now includes an Intelligent Skin-Tone Grading Exposure Algorithm, which adjusts exposure for different skin tones. This ensures better tone balance and consistent brightness, improving how skin tones are shown. These improvements work well in tricky situations like solid-colored backgrounds and backlighting.

TECNO is committed to reducing bias in skin tones and improving inclusive imaging. By continuously updating Universal Tone and growing its skin tone database, TECNO makes sure it can show a wide range of skin tones accurately.

With these updates, TECNO remains a leader in mobile imaging. After all, the brand has one of the most advanced systems for skin tone aesthetics. TECNO continues to set high standards for technology and inclusive imaging.

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