In recent years, digital images have a large variety of uses and for different purposes. The most significant and common form is called digital image forgery, which uses the same image in the forgery process, and we have many kinds of image forgeries. For creating a duplicate or hiding any existing objects, a region of an image copies and paste into the same image. For a forgery with particular form, the images are tested in this paper. Images will first be split into super pixels to detect the forgery attack. Because of the high dimensional existence of the feature space, the representation of reduced dimension feature vector is achieved with the implementation of hybrid function point mapping. During the feature matching, the efficiency is also improved. In order to identify the forgery in the picture, the suggested system is successful. The proposed method therefore offers a detecting forgery with efficiency and efficacy that helps to improve the image authenticity in evidence-centered applications.