Sensor-fingerprint based identification of images corrected for lens distortion
Sensor-fingerprint based identification of images corrected for lens distortion
复制标题
基于传感器指纹的图像识别，校正镜头畸变
DOI：
10.1117/12.909659
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发表时间：
2012
期刊：
影响因子：
--
通讯作者：
J. Fridrich
中科院分区：
文献类型：
--
作者：
M. Goljan;J. Fridrich
计算摄影正迅速从研究实验室走向市场。最近，相机制造商开始使用相机镜头对捕获的图像进行失真校正，以在紧凑且负担得起的相机中为用户提供更强大的变焦范围。由于失真校正（桶形/枕形）取决于变焦，因此它消除了在两个不同焦距处拍摄的图像之间的像素到像素的对应关系。这给利用传感器指纹（光响应不均匀性）概念的数字取证方法带来了严重的问题，例如可以将图像与特定相机匹配的“图像弹道”技术。这种技术可能会完全失败。本文提出了一种基于传感器的摄像机识别的扩展图像校正透镜失真。为了重建图像和指纹之间的同步，我们采用桶形失真模型，并搜索其参数，以最大化检测统计量，这是峰值相关能量比。所提出的方法进行了测试，从三个紧凑型相机的数百张图像，以证明该方法的可行性，并证明其效率。
Computational photography is quickly making its way from research labs to the market. Recently, camera manufacturers started using in-camera lens-distortion correction of the captured image to give users more powerful range of zoom in compact and affordable cameras. Since the distortion correction (barrel/pincushion) depends on the zoom, it desynchronizes the pixel-to-pixel correspondence between images taken at two different focal lengths. This poses a serious problem for digital forensic methods that utilize the concept of sensor fingerprint (photo-response non-uniformity), such as "image ballistic" techniques that can match an image to a specific camera. Such techniques may completely fail. This paper presents an extension of sensor-based camera identification to images corrected for lens distortion. To reestablish synchronization between an image and the fingerprint, we adopt a barrel distortion model and search for its parameter to maximize the detection statistic, which is the peak to correlation energy ratio. The proposed method is tested on hundreds of images from three compact cameras to prove the viability of the approach and demonstrate its efficiency.