With use of advanced image processing software's and tools, it becomes very easy to perform the tampering on original digital images with different intensions. Such kind of image tampering or manipulation is collectively called as image forgery. The main two types are 1) copy-move forgery and 2) image splicing forgery of image forgery. Copy-move tampering is most generally used by attackers in which object of another image is copy and paste in original image in nearly matching areas. Hence to identify such image threats, it is required to automatic computer vision based method which can classify whether input digital image is original or tampered. The image processing based methods are mainly three important phases like as image pre-processing, image features extraction and detection of forged area on image using features extracted. For copy-move forgery detection there are many methods introduced from last 15 years. This all methods are categorized in two main types is active and passive forgery detection methods. This paper scope is limited to study on passive forgery detection methods. In this paper, aim is to present the study on different old methods of image forgery detection using different approaches like DWT (Discrete Wavelet Transform), SIFT, LBP (Local Binary Pattern) etc. The outcome of this paper is to find the current research challenges based on study of different methods of image forgery detection through the comparative study of all recent methods studied. © 2017 IEEE.