Real-Time Image Forgery Detection through Machine Learning

Digital Image Forgery can be done by deceiving the digital image to mask some meaningful or important data of the image. It is usually difficult to spot out the manipulated region of the original image. To sustain the uprightness and legitimacy of the image, the detection of forgery in the image is mandatory. Acclimation of the modern way of life and advancement in photography gadgetry has made exploitation of digital image easy with the help of image editing software. Therefore, it is crucial to detect such image forgery operations in the images. The image forgery detection can be done based on object removal, object addition, and unusual size modifications in the image. Images are one of the powerful media for communication. In our project we have used algorithms such as Copy Move Technique (CMT) as existing and Multi Support Vector Machine (MSVM) as proposed systems and both will be compared in terms of accuracy