<![CDATA[With the development of digital technology, digital images can be obtained anytime and anywhere through cameras and cell phones. People can get images easily and can also manipulate the sources of information in the content and can even manipulate images. So it is necessary to verify the source of the image which is the main job in the field of image forensics. Camera source identification is the process of determining which camera device was used to take the image. Forensic Similarity approach based on Convolutional Neural Network determines if two image patches are taken by different cameras or from the same camera. This approach differs from typical camera identification in that it does not specify the exact camera used to capture any of the patches. The strength of this approach is the ability to compare cameras that were not used to train the system. This allows investigators to learn important information about images taken with any camera, and is not limited by the set of camera models in the investigator database. Although camera model information, date and time, and other information can be found in the EXIF or in the JPEG header, it is generally impossible to assume the information is correct because image metadata can be easily modified. The source camera identification process uses identification on the image to find out the camera source obtained from the image. By using a forensic similarity approach, it can support information in metadata so that it can guarantee the authenticity of the information obtained.]]>
Copyrights © 2022
