Image Processing for Partial-Region 3D Authenticity Verification
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Solution Overview
Problem
Existing image authenticity determination methods struggle to accurately detect false images generated through trick shooting or inconsistencies in focal length and distance measurement data, failing to confirm detailed subject consistency.
Innovation Solution
An image processing apparatus and method that divides an image into partial regions and compares estimated 3D information with sensor 3D information using a region division unit and comparison unit, allowing for more detailed authenticity verification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the entire image region is used for comparison, then the overall authenticity can be assessed, but detailed partial inconsistencies cannot be detected
Solution Approach 1:
The image processing apparatus divides the entire image into multiple partial regions, and compares estimated 3D information with sensor 3D information for each partial region separately. This segmentation enables detection of localized inconsistencies that would be masked when analyzing the entire image as a single unit, thereby improving authenticity determination accuracy without excessive complexity increase through systematic regional analysis
2Ease of operation
If only focal length consistency is checked, then the verification process is simple, but detailed subject inconsistencies are missed
Solution Approach 1:
The patent transitions from checking only 2D focal length consistency to incorporating 3D depth information comparison. By utilizing sensor 3D information (such as from a depth sensor or stereo camera) and comparing it with estimated 3D information derived from the image, the system adds a depth dimension to the verification process, enabling detection of subject inconsistencies that focal length alone cannot reveal
3Measurement precision
If multi-point distance measurement is performed, then plane detection is possible, but detailed unevenness consistency cannot be confirmed
Solution Approach 1:
The system divides the image into multiple partial regions and performs 3D information comparison for each region. This segmentation allows the detection of local depth inconsistencies and surface unevenness variations that would be averaged out in whole-image analysis, providing detailed confirmation of subject consistency without requiring an excessively complex measurement system
Data Source
AI summary
Image processing with improved image authenticity is disclosed. In one example, a partial region is generated by dividing an entire region of an image, and estimated 3D information is compared with sensor 3D information with use of the partial region. The estimated 3D information is 3D information estimated on the basis of the image, and the sensor 3D information is 3D information acquired by a sensor and associated with the image.