Identifying Image Modifications using DCT and JPEG Quantization Technique

Prajakta Kubal, Namita D. Pulgam, V. Mane
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Abstract

The volume of images and the videos are being shared on various social media platform are huge and there are cybercrimes happening in these areas. Hence, identification of the main source of social network, based on the images uploaded or downloaded from social network has become an important activity in the multimedia forensic analysis. When media shared on social network there are possibilities of exploiting different pattern embedding in image content by social network. To make it easier system is proposed with discrete cosine transform (DCT) method and JPEG Quantization to identify the changes in shared images on social networks applications. The quantization used in JPEG compression is used to help in separating the images that have been processed by software. DCT finds the pixel value of the blur images and it is easier in implementation. The combination of DCT and JPEG quantization can give the better accuracy rate which helps in finding the images shared or the source of the images.
利用DCT和JPEG量化技术识别图像修改
在各种社交媒体平台上分享的图像和视频数量巨大,这些领域发生了网络犯罪。因此,基于社交网络上传或下载的图像来识别社交网络的主要来源已经成为多媒体取证分析中的一项重要活动。当媒体在社交网络上分享时,社交网络有可能利用图像内容中嵌入的不同模式。为了便于识别,提出了一种基于离散余弦变换(DCT)和JPEG量化的系统来识别社交网络应用中共享图像的变化。JPEG压缩中使用的量化是用来帮助分离经过软件处理的图像。DCT可以找到模糊图像的像素值,实现起来更容易。将DCT与JPEG量化相结合,可以获得更好的准确率,有助于找到共享图像或图像的来源。
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