Image Forgery Detection Model using CNN Architecture with SVM Classifier
Surjeet Singh, Vivek Kumar Sehgal · 2022
This Due to rapid advancement in computer vision system and easy availability of digital camera’s acquisition of images and sharing the content on social media platform with falsify content is challenging task to the researcher community. For the legal purpose to provide the evidence in court, it’s a difficult task identify the forgery in image that why various traditional artefacts of capturing device and internal footprints of image used to check the forgery in original image. Now a day’s easy availability of software editing tools the captured image modify with wrong content to defame the person or misleading the people on social media with fake content. In this article, proposed a CNN based architecture to classify the forgery in given image. CNN architecture is capable to detect the unseen forgeries based on features extracted through various convolution layers and used SVM classifier to classify the label of forged image with high accuracy.