| Sumario: | Image processing is leading in some of the important areas like science and technology, biological, agriculture, face recognition and other fields. The main aim of machine learning is to improve or compress the image data. It is used to minimise a loss or cost function by optimising differentiable parameters. As a result of combining these two, a greater understanding of image processing has emerged. On other hand improving the image data in machine learning is one of the factors on other hand Image are one of the most common sharing things on the internet. In this emerging era many fake images are also sharing with the real images. Forging the images leads to the cybercrimes, So the area of detecting forging images is difficult task. The tampered images are identified using the neural networks that recognizes a section of an original image that has been manipulated. The false content in a fake image has a different compression ratio than the original image that can be identified by using Error Level Analysis.
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