Image Sensor Noise Fingerprinting for Clone-Resistant Image Data
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Solution Overview
Problem
Existing image sensors face challenges in ensuring the uniqueness of image data, as captured images can be cloned, and the identity of the image sensor from which they were obtained cannot be determined.
Innovation Solution
An image processing device generates a physical intrinsic identification key for a target image sensor based on noise information from adjacent pixels, using a noise information manager, a physical intrinsic identification key generator, and an intrinsic image generator to create intrinsic image data with a unique identifier.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If image data is generated using conventional image sensors, then image acquisition is achieved, but the image data can be cloned and uniqueness cannot be ensured
Solution Approach 1:
The patent converts the harmful fixed pattern noise (which causes image degradation) into a beneficial authentication feature. By extracting and utilizing the noise characteristics from adjacent pixels, the system creates a unique identifier that proves the image was captured by a specific physical sensor, making cloned images detectable while maintaining normal image quality through post-processing correction.
2Reliability
If a unique identifier is added to image data, then image uniqueness is ensured, but the device complexity increases
Solution Approach 1:
The system performs self-identification by extracting the unique identifier from the image sensor's own noise characteristics. The physical intrinsic identification key is generated automatically by analyzing the fixed pattern noise in adjacent pixels during normal image acquisition, eliminating the need for external authentication systems or additional hardware components.
Solution Approach 2:
The patent extracts only the essential noise information from adjacent pixels to create a compact unique identifier. By selecting and extracting specific noise characteristics rather than processing the entire image data, the system achieves uniqueness authentication with minimal additional processing complexity and computational overhead.
3Measurement precision
If noise information from adjacent pixels is used to generate identification key, then image sensor identity can be determined, but measurement precision requirements increase
Solution Approach 1:
The system employs feedback mechanisms to continuously monitor and validate the noise characteristics during image acquisition. By comparing the extracted noise patterns against expected characteristics and adjusting the identification key generation process accordingly, the system maintains high measurement precision while ensuring reliable sensor identification even in varying environmental conditions.
Data Source
AI summary
An image processing device may include: a noise information manager for managing noise information of a target image sensor and a reference image sensor. It may also include a physical intrinsic identification key generator, which generates a physical intrinsic identification key of the target image sensor, based on a difference between noise signals output from pixels of the target image sensor that are adjacent to each other. An intrinsic image generator generates intrinsic image data, which includes the physical intrinsic identification key of the target image sensor.