License Plate and Face Blurring for Railways and Roadway Operators

TL;DR: Gallio PRO automatically blurs faces and license plates in recorded railway and roadway camera footage, on your own servers. It is built for DPOs, security officers and ITS managers at rail carriers and road authorities who must release or archive monitoring material without exposing third parties. Processing is on-premise, no detection logs are kept, no personal data is stored.

Modern transport systems rely heavily on high-resolution video monitoring for safety, maintenance and traffic management. Cameras installed along roads, railway tracks and stations record millions of frames daily, often capturing identifiable faces and license plates. To meet the standards of the General Data Protection Regulation (GDPR) and protect individual privacy, transport operators need automated roadway and railway video anonymization. Gallio PRO delivers AI-powered, motion-aware anonymization of recorded footage that supports compliance without compromising operational performance or data quality.

Why Rail and Road Operators Need Anonymization?

Visual monitoring in transport infrastructure plays a critical role in security, maintenance and operational efficiency. Station cameras capture commuters and staff, while roadway cameras record vehicles for incident detection, tolling and analytics. Under Article 4(1) of the GDPR, an image from which a person can be identified, directly or indirectly, is personal data. A readable license plate falls in the same category, because it can be linked to a registered keeper: a point covered in more depth in our glossary entry on automated license plate recognition and privacy.

Two obligations drive most anonymization work in this sector.

The first is data subject access. Article 15 gives individuals the right to receive a copy of their personal data, including monitoring footage. Article 15(4) adds that this right must not adversely affect the rights and freedoms of others, so a recording released to one person cannot expose the faces and plates of everyone else in the frame.

The second is reuse. Footage collected for safety monitoring is frequently reused for analytics, AI model training or public communication. Recital 26 of the GDPR states that data protection principles do not apply to information rendered anonymous in such a way that the data subject is no longer identifiable. Irreversible blurring of faces and plates is what moves a recording toward that threshold, allowing safe secondary use.

AI-Powered Motion-Aware Anonymization

Gallio PRO is designed for transportation environments where vehicles and people move at high speeds. Traditional blurring tools struggle to detect fast-moving objects or to maintain frame-to-frame consistency. The motion-aware anonymization engine in Gallio PRO uses AI-based object tracking to follow faces and license plates in motion, producing smooth and accurate masking even under complex lighting or weather conditions.

The system adapts to different recording contexts: static cameras at intersections, moving cameras on inspection trains, or mobile surveillance vehicles. It applies adaptive blur intensity and motion prediction to keep anonymization stable across high-speed sequences.

Note that Gallio PRO uses face detection, not facial recognition. The software locates a face in the frame in order to obscure it. It does not identify who that person is, and it does not build or query any biometric template.

Batch Processing for Transport Systems

Gallio PRO uses batch processing for transport networks. Footage exported from station, toll or on-board cameras is anonymized on your own infrastructure, so raw identifiable footage never leaves your control. Live camera feeds are not processed. Large volumes of recorded data, for instance from rail inspection or roadway patrol vehicles, can be anonymized automatically before archival or analysis.

This lets railway and roadway operators build privacy protection into existing operational workflows while maintaining efficiency and compliance.

How to Anonymize Railway and Roadway Footage with Gallio PRO

1. Export the recording from your VMS. Pull the required time window from your video management system in a standard container. Gallio PRO works on exported files, not on live streams.
2. Load the material into Gallio PRO on your own server. The application runs inside your infrastructure, so the source file stays within your network the entire time.
3. Select the detection scope: faces, license plates or both. For an Article 15 access request, both are normally required. For a public communication clip, faces are often the primary concern.
4. Run automated detection and review the result. Gallio PRO marks and blurs detected objects across frames. Use the manual editor to add anything the automatic detection does not cover, for example a name board or a document visible in shot, since automatic detection covers faces and plates only.
5. Export the anonymized version and archive it. The blurring is burned in and irreversible. Retain the anonymized file and apply your retention policy to the original.
6. Record the operation in your own processing records. Gallio PRO keeps no detection logs and stores no personal data, so your internal register is the evidence base for Article 5(2) accountability.

On-Premise Processing for Maximum Data Control

All anonymization with Gallio PRO takes place on-premise, inside the operator's own IT infrastructure. Raw footage never leaves secure environments, which supports the Article 32 requirement for appropriate technical and organizational measures. Operators keep full control over storage, access rights and retention policies, and avoid the exposure that comes with transferring visual material to an external processor.

Because the software keeps no detection logs and stores no personal data of its own, there is no secondary copy of identifiable material to secure, audit or delete. Your existing records of processing activities remain the single source of truth for accountability.

Handling High-Speed and Complex Environments

Rail and roadway systems present specific technical challenges: motion blur, reflections, varying lighting conditions and high object density. The deep-learning models in Gallio PRO are trained for these environments, so detection of faces and license plates stays reliable in motion-heavy scenes. The AI adapts to different camera positions, including:

• Fixed infrastructure cameras monitoring stations, tunnels or intersections.
• Mobile cameras mounted on trains, trams or road patrol vehicles.
• Pan-tilt-zoom (PTZ) cameras used for incident response or maintenance operations.

Predicting motion vectors keeps anonymization consistent across frames and prevents the flickering or gaps typical of static blurring systems.

Operators running camera fleets on the vehicles themselves, rather than on fixed infrastructure, face a different set of workflow questions around upload, scheduling and retention. Those are covered separately in our guide to dashcam and fleet camera anonymization.

Compliance with GDPR and Transport Regulations

As public infrastructure operators, rail and road authorities work under strict data protection principles. Articles 5, 6 and 32 of the GDPR require a lawful basis, minimization and adequate safeguards when processing visual data for purposes such as safety monitoring or operational analytics. The EDPB Guidelines 3/2019 on processing of personal data through video devices set out how supervisory authorities read these obligations for camera systems specifically.

Gallio PRO supports compliance by anonymizing faces and licence plates locally, while keeping no detection logs and no personal data. Reporting to Data Protection Officers and readiness for audits rest on your own processing records, not on data held by the software.

Case Studies: Rail and Road Operators Using Gallio PRO

PKP Intercity, nationwide rail carrier. PKP Intercity operates in the critical infrastructure sector, where a distributed work environment and large-scale operations make visual documentation hard to standardize. Its Material and Personnel Security Office uses Gallio PRO to anonymize material used in investigations and security analyses. According to Marcin Hasir, Chief Specialist in the Security Bureau, automation shortened anonymization time for documents and visual materials by 50 to 60 percent, reduced errors from manual blurring and produced a uniform anonymization standard across units. Full details are in the PKP Intercity case study.

MZUiM Katowice, municipal streets and bridges authority. The Katowice Intelligent Transport System operates the city's monitoring cameras. When an individual submits an Article 15 access request for footage, the authority must supply the recording without disclosing third parties in the same frame. Gallio PRO automates that step by hiding vehicle registration numbers and people's images before release. Pawel Pluszke, ITS Department Manager, reports that automating the process significantly reduced the time needed to prepare recordings for requesters. Full details are in the MZUiM Katowice case study.

Integration with Traffic and Rail Management Systems

Gallio PRO fits alongside existing Video Management Systems (VMS) and transportation analytics platforms. Anonymization runs on exported material in local control centres or data warehouses, which keeps existing workflows intact and limits system disruption during deployment.

Operators can configure anonymization profiles by location or camera type, for instance different blur settings for tunnel cameras versus highway checkpoints, creating a consistent yet flexible privacy framework across the network.

Safeguarding Privacy in Modern Transport Networks

As transportation systems become more data-driven, public trust and privacy protection go together. Gallio PRO lets rail and road operators process visual data responsibly, with anonymization built for the specific challenges of motion and speed.

Adaptive detection, motion prediction and on-premise processing mean anonymized footage keeps its analytical and operational value while identifiable detail is removed.

Download Gallio PRO and test it on your own railway or roadway footage, on your own infrastructure, before you commit.

FAQ: Roadway and Railway Video Anonymization

What is roadway and railway video anonymization?

It is the automated detection and masking of faces and license plates in recorded transport footage, so that the material can be shared, archived or analysed without exposing identifiable individuals.

Is anonymization applied in real time?

No. Gallio PRO anonymizes recorded video. Live camera feeds are not processed.

Can anonymization handle high-speed footage?

Yes. Gallio PRO uses motion-aware AI that tracks and blurs fast-moving faces and plates consistently across frames.

What does Gallio PRO detect automatically?

Faces and license plates. Anything else that needs to be obscured, for example a document or a name board visible in shot, is handled in the manual editor.

Does Gallio PRO require cloud access?

No. All anonymization occurs on-premise, keeping raw footage within your infrastructure.

Can anonymization affect incident analysis?

No. Gallio PRO preserves motion, trajectory and scene context while removing identifiable details.

How do operators verify GDPR compliance?

Through their own records of processing activities. Gallio PRO keeps no detection logs and stores no personal data.

Is the blurring reversible?

No. The anonymized export has the blur burned in, so the identifiable version cannot be recovered from it.

Bibliography

• European Data Protection Board (EDPB), Guidelines 3/2019 on Processing of Personal Data through Video Devices, 30 January 2020. Available at: edpb.europa.eu
• Regulation (EU) 2016/679, General Data Protection Regulation (GDPR), Official Journal of the European Union. Available at: eur-lex.europa.eu
• CNIL, Practice Guide: Security of Personal Data, 2024 Edition. Available at: cnil.fr
• Information Commissioner's Office (ICO), Guidance on Video Surveillance (Including CCTV). Available at: ico.org.uk