Image Reconstruction via RST Vector Alignment
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Solution Overview
Problem
It is challenging to reconstruct original content from degraded content shared through channels like social networks due to deformation and degradation during capture and compression, making it difficult to extract continuous feature codes and detect watermarks effectively.
Innovation Solution
A method that involves selecting feature points in both original and degraded content images, generating reference vectors, calculating rotation, scale, and transformation (RST) values to correct and reconstruct the degraded content, and detecting watermarks in the reconstructed images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If content is shared through social network services, then content distribution and accessibility are improved, but content resolution and image quality are degraded
Solution Approach 1:
The system performs preliminary actions by embedding watermarks and extracting feature codes into the original content before distribution. This ensures that even when content is degraded during sharing, the embedded identifiers remain intact and can be used to reconstruct and identify the original content later.
Solution Approach 2:
The system creates a digital copy or representation of the original content's identifying features (watermarks and feature codes) that can survive degradation. By copying these essential identifiers into the shared content, the system enables reconstruction of original content attributes even from degraded versions.
2Loss of information
If continuous feature code extraction is attempted from degraded content, then content identification is pursued, but extraction accuracy becomes insufficient
Solution Approach 1:
The system extracts feature codes and embeds watermarks into the original content before degradation occurs. This preliminary extraction ensures high-accuracy capture of content identifiers when the content is still in its original, undegraded state, avoiding the accuracy loss that would occur if extraction attempted on degraded content.
Solution Approach 2:
The system uses watermarks as an intermediary carrier that preserves feature code information through degradation. The watermark acts as a mediator between the original content and the degraded shared content, maintaining extractable identifier information even when the visual content quality deteriorates.
3Reliability
If watermark detection is performed on degraded content, then copyright protection is pursued, but detection reliability becomes insufficient
Solution Approach 1:
The system performs preliminary watermark embedding into the original content before distribution and degradation. By establishing the watermark in the source material when conditions are optimal, the system ensures detection reliability is maximized before harmful degradation occurs.
Solution Approach 2:
The system converts the harmful effect of content degradation into a benefit by designing watermarks that are specifically engineered to survive or even become more detectable after degradation. The degradation process, while harmful to visual quality, does not destroy the watermark's detectability, allowing reliable copyright protection despite the harmful factors.
Data Source
AI summary
Provided is a method for reconstructing content image data. The method includes selecting a first point and a second point in a first image of first content, selecting a third point and a fourth point in a second image of second content (the second image is an image corresponding to the first image and the third point and the fourth point are points in an image corresponding to the first point and the second point, respectively), generating a first reference vector using the first point and the second point, generating a second reference vector using the third point and the fourth point, calculating a rotation, scale, and transformation (RST) value from the first image to the second image using the first reference vector and the second reference vector; and reconstructing the second content using the calculated RST value.