International Journal of Science and Research (IJSR) ISSN (Online): 2319-7064 Index Copernicus Value (2013): 6.14 | Impact Factor (2013): 4.438 Volume 4 Issue 3, March 2015 www.ijsr.net Licensed Under Creative Commons Attribution CC BY A Survey on Copy Move Image Forgery Detection Using Wavelet Transform Akanksha Namdeo 1 , Anish Vishwakarma 2 1 Rungta College of Engineering and Technology, Department of Electronics Engineering, Kohka-Kurud Road, Bhilai 490024, India 2 Rungta College of Engineering and Technology, Department of Electronics and Engineering, Kohka-Kurud Road, Bhilai 490024, India Abstract: Editing of images are very common these days. The process of creating fake images has been very simple with the introduction of powerful computer graphics. Such tempering with digital images is known as image forgery. With the advancement of the digital image processing software and editing tools, a digital image can be easily forged. The detection of image forgery is very important because an image can be used as legal evidence, in investigations, and in many other areas. The pixel-based image forgery detection aims to verify the authenticity of digital images without any prior knowledge of the original image. There are many different ways for tampering an image such as splicing or copy-move, resampling an image that are resize, rotate, stretch, addition and removal of any object from the image. In this we have discussed various pixel-based techniques for image forgery detection. Keywords: Forgery Detection, Dydic Wavelet Transform,Discrete Wavelet Transform,SVD,Image Forencics.. 1. Introduction Digital Image forgery is the process of altering or manipulating a digital image with an intention to mislead others by representing the changes as true copies of the original. The advancement in technology introduces us many digital image editing softwares such as Photoshop, Gimp Fireworks etc. which helps in editing the images without making any visible traces of forgery. So the maintenance of integrity and authenticity of digital images is a major problem. The main goal of this paper is:  to introduce various ways of image forgery detection;  to review some existing techniques in pixel-based image forgery detection;  to provide a comparative study of existing algorithms with their merits and demerits. Digital image forgery detection techniques are classified into active and passive approaches. In the active approach, the digital image requires preprocessing of image such as watermark embedding or signature generation, it limits their application in practice, Unlike the watermark and signature- based methods, the passive techniques are not need any digital signature to be generated or to embed any watermark. Passive image forgery detection techniques roughly can be divided into five categories: 1.Pixel-based image forgery detection: Pixel-based techniques detect statistical anomalies introduced at the pixel level Pixel-based techniques emphasize on the pixels of the digital image. This is one of the most common forgery detection techniques. These techniques are categorized into four types. a) Copy move b) Resampling c) Splicing d) statistical 2. Format-based image forgery detection: format-based techniques leverage the statistical correlations introduced by a specific lossy compression scheme. Format based techniques are another type of image forgery detection techniques. These are based on image formats mainly in the JPEG format. These can be divided into three types. If the image is compressed then it is very difficult to detect forgery but these techniques can detect forgery in the compressed image. a) Jpeg Quantization b) Double Quantization c) Jpeg Blocking 3. Camera-based image forgery detection: camera- based techniques exploit artifacts introduced by the camera lens, sensor, or on-chip post-processing. Whenever we capture an image from a digital camera, the image moves from the sensor to the memory of camera and it undergoes a series of processing steps, quantization, colour correlation, white balancing, filtering, and JPEG compression. These processing steps starts with capturing to end with saving the image in the memory may vary on the basis of camera model and artifacts of camera. These techniques work on this principle. These techniques can be divided into four categories. a) Chromatic aberration b) Color filter array c) Camera response d) Sensor noise 4. Physical environment-based image forgery detection: physical environment-based techniques explicitly model and detect anomalies in the 3-D interaction between physical objects, light, and the camera. Consider the creation of a forgery showing two movie stars, rumored to be romantic seans, walking down a sunset beach. Such an image might be created by splicing together individual images of each movie star. In doing so, it is often difficult to exactly match the lighting effects under which each person was originally photographed. Differences in background lighting across an image can then be used as evidence of tampering. These algorithms work on the basis of the lighting environment under which an object or image is captured. Background Paper ID: SUB152000 876