Digital Image Pixel Row Segmentation for Authentication
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Solution Overview
Problem
Conventional digital forensic techniques are unable to authenticate every individual pixel in a digital image, making it difficult to detect alterations such as cloning, resampling, or splicing.
Innovation Solution
The method involves encoding a digital image by partitioning it into multiple pixel rows, generating and overlaying codes within specific rows, and encoding these codes into the remaining pixel row, allowing for later detection of any pixel alterations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional digital forensic techniques are used, then statistical analysis can detect some alterations, but individual pixel authentication is not possible
Solution Approach 1:
The patent divides the digital image into multiple segments (first plurality of pixel rows, second plurality of pixel rows, and remaining pixel row) and processes each segment separately to generate distinct codes. This segmentation enables individual pixel authentication by creating verifiable code representations of specific image portions, directly addressing the limitation of conventional techniques that cannot authenticate individual pixels.
Solution Approach 2:
The patent embeds authentication codes into the image during the encoding phase, before any potential alterations occur. By pre-processing the image to include verification codes in the remaining pixel row that correspond to the first and second pixel row groups, the system enables later detection of alterations without requiring complex analysis during the authentication phase.
2Reliability
If encoding codes are embedded in the image, then pixel alteration detection becomes possible, but image processing complexity increases
Solution Approach 1:
The patent introduces codes as intermediary elements that mediate between the image content and the authentication process. These codes, embedded in the remaining pixel row, serve as verifiable representations of the first and second pixel row groups, enabling reliable integrity verification without requiring direct complex analysis of the entire image during authentication.
Solution Approach 2:
The patent creates code representations (copies) of the first and second pixel row groups and embeds these codes into the remaining pixel row. These code copies contain the essential information needed for authentication, allowing verification of image integrity without requiring the original pixel data during the authentication phase, thus simplifying the verification process.
3Measurement precision
If multiple codes are generated and encoded into the image, then detection precision improves, but processing time increases
Solution Approach 1:
The patent generates multiple distinct codes (first code from first pixel rows, second code from second pixel rows, and third code from remaining row) to enable precise detection of alterations in different image portions. This segmentation approach allows targeted verification of specific image regions, improving detection precision while maintaining efficient processing by focusing on code comparison rather than entire image analysis.
Solution Approach 2:
The patent transforms image data into code representations with specific parameters (first code, second code, third code) that can be efficiently compared for authentication. By changing the parameter representation from raw pixel data to condensed codes embedded in the remaining pixel row, the system achieves high detection precision with reduced processing time during authentication.
Data Source
AI summary
An encoding apparatus partitions a digital image into multiple regions for subsequent encoding. A first encryption code is associated with a first region, a second encryption code is associated with a second region and the first code, and a third code is associated with the first code, the second code and a third region. An authentication apparatus authenticates the digital image in an inverse process.