Novel video camera authentication based on peak to correlation energy of clustered sensor pattern noise

Now a days the technology of digital media is growing very rapidly. As the cost of digital imaging devices falls and the functionalities of these devices increase, digital imaging become increasingly cheaper in our every-day life. Also powerful easy-to-use digital image processing tools provide effective means for manipulating images that can serve good and malicious purposes. As a result, the use of digital images in forensic investigations becomes more frequent and important. Typical image forensics includes digital camera identification. In recent years, a digital camera identification method using the sensor pattern noise has received considerable attention. Photo-response non uniformity (PRNU) noise is due to varying sensitivity of pixels to light and it is unique to device, serves as the fingerprint of a camera. However, the PRNU noise of an image is usually contaminated by random noise and scene content and affected by the image processing engine, which inhibits stable identification in earlier researches. In this paper, we propose a novel digital camera identification method based on combined decision of pair wise relation of clustered PRNU and clustered Peak to correlation energy, which are robust to noise contamination and decreases false acceptance rate.