Detection of incorrect and inappropriateImagefrom Tweets in Social Network

Abstract

Digital imaging has grown to become the prevalent technology for creating, processing, and storing digital memory and proof. Though this technology brings many leverage, it can be used as a ambiguous tool for covering details and evidences. This is because today digital images can be tampered in such supremacy that forgery cannot be find visually. In fact, the immunity concern of digital content has arisen a long time ago and different methods to verify the efficiency of digital images have been developed. Digital images offer many features for forgery detection algorithm to take precedence of specifically the color and brightness of individual pixels as well as an image�s resolution and format. These properties grant for analysis and similarity between the significance of digital forgeries in an attempt to develop an algorithm for detecting image tampering. This paper presents a technique for image copy or move image forgery detection using Radix Sort, FasterK-means clustering algorithm & DCT.