Photo Authenticity Verification

Photo authenticity verification based on evidentiary context. A transparent and reproducible method that audits the circumstances of capture—time, location, and associated device data—without analyzing image pixels.

Online Capture Context Verification by Identifier

To begin verification, enter the photo's unique identifier (PUBLIC UID) and start the check. The system will display the dataset generated at the moment of capture and during subsequent processing. This data reveals when, under what conditions, and as part of which process the photo was taken. Important: Verification does not perform a visual analysis of the image. It displays the evidentiary context linked to the photo's creation process.

Public Identifier (PUBLIC UID)

Data Displayed and How It Helps Verify Context

PUBLIC UID — Public Photo Identifier

A unique identifier used to perform the verification. It unequivocally links the photo to a system record and prevents substitution with another image.

client_captured_at — Device Capture Time

Reflects the moment of capture according to the user's device time. This field allows you to:

Establish event chronology;
Correlate the photo with the claimed work completion time;
Detect attempts at backdating.

is_verified — Image Integrity Status

Indicates whether the photo has been altered after capture.

true — The image has not been modified after creation within the app;
false — The photo has been edited or resaved after capture.

Important: A value of false does not imply context unreliability but indicates the visual integrity of the image file has been compromised.

timezone — Capture Time Zone

Displays the time zone in which the capture time was recorded. This enables correct interpretation of temporal data and eliminates errors related to different time zones.

lat and lon — Capture Coordinates

Latitude and longitude recorded at the moment of capture. Used for:

Verifying spatial context;
Matching the photo to an inspection object or zone;
Analyzing logical consistency of routes and actions.

gps_accuracy — Coordinate Accuracy

Shows the location determination margin of error in meters. Allows assessment of coordinate reliability and understanding of the conditions under which they were obtained.

address — Capture Address

Displayed as a string address determined at the moment of capture. Used for human-readable verification and matching with the claimed work location.

model — Device Model

Identifies the device used for capture. This is important for:

Analyzing data acquisition conditions;
Detecting anomalies;
Confirming the use of an actual mobile device.

platform — Device Operating System

Specifies the OS on which the app was running during capture (e.g., Android or iOS). Helps correctly interpret data collection specifics.

app_version — Application Version

Records the app version used to take the photo. This accounts for changes in data recording logic between versions.

created_at — Record Creation

The moment the record was created in the system. Used to verify consistency between server time and client data.

updated_at — Record Update

Shows if the record was updated after creation. This helps understand whether metadata was changed and when.

The displayed fields collectively form the evidentiary capture context, separating verifiable facts from interpretations and assumptions.

What 'Photo Authenticity Verification' Means

Photo authenticity verification is not an attempt to 'guess' if a photo is real, nor is it pixel analysis. Within the INSPECTOR project, authenticity refers to the reliability of the capture context: confirming when, where, under what conditions, and under what circumstances a photo was taken, and clarifying which facts can be confirmed and which fundamentally cannot.

The app deliberately separates context verification from:

AI-based image analysis;
Searching for pixel editing traces;
Subjective assessment of image content.

The app's goal is to provide the user with verifiable and reproducible evidence, not interpretations.

What Can Be Verified About a Photo

1. Capture Context

A photo's context is the set of conditions under which it was taken. Context verification can confirm:

The time the image was created;
The sequence of events before and after capture;
The photo's connection to a specific report, task, or event;
The continuity of the documentation chain (when and by whom actions were performed);
The photo's alignment with the stated purpose of capture.

Important: This refers not to the 'truthfulness of the image,' but to the truthfulness of claims made about it.

2. Capture Conditions

We can confirm:

That the photo was taken by the user, not uploaded externally;
That capture occurred within a recorded workflow;
That the photo was obtained at a specific moment, not retroactively;
That the user's actions during capture followed the defined process.

This is especially important for:

Reporting photos;
Documentation of completed work;
Inspections, audits, and surveys;
Recording object conditions.

3. Associated Data (Evidentiary Context)

A photo is considered not in isolation but as part of a dataset. The following can be verified:

User actions before and after capture;
The logic of transitions between process steps;
The fact of image saving, transfer, and use;
The immutability of the recorded context after image creation.

This layer of data forms the photo's evidentiary context.

What Cannot Be Verified About a Photo

1. Image Content

We do not assert and do not verify:

That the depicted object is 'real';
That the event in the photo happened exactly as a viewer interprets it;
That the photo contains no staged elements;
That the image cannot be visually simulated.

Any visual interpretation remains subjective.

2. Absence of Pixel Editing

Photo authenticity verification is not equal to an edit check. We do not claim:

That the image was not processed by graphics editors;
That the image shows no signs of correction;
That the photo is 'original' in a technical sense.

Even a fully edited image can have a reliable capture context if that context was correctly recorded.

3. Intentions and Interpretations

A photo does not prove:

Motives for actions;
Causes of an incident;
Legal standing of parties;
Assessment of event consequences.

Context confirms facts but does not substitute for conclusions.

How We Authenticate Capture Context

Principle

The authenticity of a photo's context is confirmed not by the image itself but by the process of its creation. The key principle: > If the process is recorded, reproducible, and consistent—the context can be considered demonstrable.

Stages of Forming Evidentiary Context

Scenario Recording — The photo is taken not arbitrarily but as part of a defined action.
Sequence Control — User actions are recorded in a logical chain.
Link to Subject of Inspection — The photo is tied to a specific task, object, or report.
Immutability After Creation — Context cannot be rewritten retroactively.
Reproducibility — An independent party can understand how and under what conditions the image was taken.

How Context Verification Differs from AI Analysis

Context Verification	Image Analysis
Verifies conditions	Analyzes pixels
Process-based	Probability-based
Reproducible	Often non-deterministic
Explainable	Model-dependent
Suited for reports	Suited for filtering

Context verification does not replace AI but solves a different problem.

Practical Applications

Inspections and Audits

Photo reports on object condition;
Work completion monitoring;
Technical surveys;
Inspector verifications.

Context is more important than the image's appearance.

Business and Contractors

Confirming service delivery;
Client reports;
Resolving disputed situations;
Managing remote contractors.

Journalism and Research

Confirming image provenance;
Verifying material acquisition conditions;
Distinguishing facts from interpretations.

Legal and Expert Environments

Preliminary assessment of photo evidence;
Analysis of accompanying conditions;
Precluding context substitution.

Important: Context verification does not replace expert examination but increases transparency.

Method Limitations

We explicitly state the limitations:

Context is not equal to truth;
A photo does not prove an event in its entirety;
Any conclusions require interpretation;
The method is not intended for visual forensics.

Openly stating boundaries increases trust in the results.

Summary

Photo authenticity verification by context is a method to:

Separate facts from assumptions;
Confirm capture conditions and process;
Record evidentiary context;
Honestly show what can and cannot be proven.

It is this transparency and reproducibility that make such verification valuable for users, businesses, and professional communities.

Photo Authenticity & Context Verification

In which situations is photo authenticity verification most needed?

Context verification is particularly valuable in fields where photographic evidence supports critical decisions or records, such as: construction progress claims, insurance damage assessments, property condition inspections, compliance auditing, supply chain documentation, and preliminary legal evidence gathering. It adds a layer of accountability to visual documentation.

Can you verify a photo's authenticity without analyzing the image itself?

Yes. Our context verification method does not analyze image pixels for manipulation. Instead, it examines and validates the documented circumstances of the photo's creation: the precise when, where, and how it was taken, based on data captured by the device and app during the shooting process.

Do you check if a photo has been edited?

No. The context verification process is not designed to detect image editing (e.g., Photoshop alterations). A photo can be edited yet still have a verifiably authentic creation context if it was captured and documented correctly within our system at the claimed time and place.

How is context verification different from AI image analysis?

AI image analysis interprets visual content, often making probabilistic judgments about objects or manipulations. Context verification relies on recorded, factual device and process data (timestamps, location, device IDs) that form a reproducible audit trail. This makes it explainable and based on concrete, recorded events rather than visual interpretation.

Can you prove the exact location where a photo was taken?

Context verification confirms the location data (GPS coordinates) that was recorded by the device at the moment of capture. It confirms what the device reported, not the absolute geographical truth. Factors like GPS accuracy or spoofing are noted as part of the transparency report, so users can assess the reliability of the location data provided.

Is this verification suitable for legal or expert tasks?

Context verification does not replace a formal forensic expert examination. However, it provides a robust, supplementary source of transparent and reproducible metadata. This data can be valuable for internal audits, dispute resolution, and providing supporting documentation for expert analysis by offering a clear record of the photo's provenance.

Can the shooting context be faked?

Our system is designed to prevent retroactive alteration of the core contextual data (time, device ID, sequence). While no system can guarantee 100% impermeability against all possible attacks (e.g., a rooted device), the model is built to make post-hoc forgery economically and practically unviable for most real-world scenarios by securing the data chain at capture.

Does verifying the context prove an event actually happened?

No. Context verification confirms the circumstances under which a digital photo file was created on a specific device. It does not, and cannot, independently prove that the event depicted in the photo's content objectively occurred in reality. It verifies the digital provenance, not the content's truth claim.