Image Tampering Detection via Block Segmentation and Feature Encoding
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Solution Overview
Problem
Existing image tampering detection technologies are limited to detecting single types and formats of tampering, relying on JPEG compression traces and lacking robustness across different tampering types, which compromises accuracy.
Innovation Solution
A method and system that segment images into small fragments, extract initial features, and encode them using a predetermined encoder to generate complex features for accurate detection of various tampering types and formats, independent of JPEG compression traces.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If existing tampering detection algorithms are used, then single types of tampering can be detected, but the detection capability is limited to single types and formats
Solution Approach 1:
The image is divided into multiple small fragments through block segmentation, and each fragment is processed independently to extract features. This segmentation enables the system to handle various tampering types by analyzing local characteristics of different image regions separately.
Solution Approach 2:
The encoder is designed to extract universal features that are applicable across different tampering types and image formats. By learning robust feature representations that generalize beyond single tampering scenarios, the system achieves multi-functional detection capability while maintaining high accuracy.
2Adaptability or versatility
If JPEG compression trace-based algorithms are used, then JPEG format tampering can be detected, but other image formats cannot be detected
Solution Approach 1:
The algorithm transitions from relying on JPEG-specific compression parameters to learning format-agnostic features through the encoder. By changing the detection parameters from format-specific traces to universal feature representations, the system can accurately detect tampering across multiple image formats including JPEG, PNG, and others.
3Difficulty of detecting and measuring
If complicated feature extraction is used, then feature extraction can be performed, but the extracted features lack robustness for changes of tampering types
Solution Approach 1:
The encoder employs dynamic feature extraction that adapts to different tampering types rather than relying on static, pre-defined features. The system dynamically learns relevant features during training, enabling robust detection across varying tampering scenarios while simplifying the extraction process through automated learning.
Data Source
AI summary
A method and system of detecting image tampering, an electronic device and a storage medium. The method includes: A. carrying out block segmentation on a to-be-detected image to segment the to-be-detected image into a plurality of image small fragments, and extracting initial tampering detection features from all the image small fragments; B. encoding the extracted initial tampering detection features with a predetermined encoder to generate complicated tampering features, and determining a tampering detection result corresponding to the to-be-detected image according to the generated complicated tampering features, wherein the tampering detection result includes an image-tampered result and an image-not-tampered result. The disclosure realizes accurate detection for different types and formats of image tampering.