文章基本信息

标题：An Efficient Method for Detecting Forged Images Using Fuzzy Based Framework Theory
本地全文：下载
作者：M. Ramya
期刊名称：International Journal of Computer Trends and Technology
电子版ISSN：2231-2803
出版年度：2014
卷号：12
期号：1
页码：1-5
DOI：10.14445/22312803/IJCTT-V12P101
出版社：Seventh Sense Research Group
摘要：In the growing of digital photography, manufacturers of graphic editing tools quickly catch up momentum. The tools are becoming cheaper and easier to use so easy in fact that anyone can use them to enhance their images. Editing or postprocessing, if done properly, can greatly enhance the appearance of the picture, increase its impact to the viewer and better convey the artist’s message. To address these issues five different forgery detection algorithm has been used. a certain image which is exposed to forgery can be detected by using those four different algorithms such as Misaligned JPEG Compression, Double Quantization Effect, Misaligned JPEG G. The results from these algorithms were classified using neural network classifier. In this we proposed the Fuzzy Theory framework which is based on the Fuzzy theory as results of different tools are considered and taken decision. Within the Fuzzy Theory framework formalism not only the problem of different number of classes can be solved, but also the relative reliability of the classifiers can be taken into consideration.
关键词：Forgery detection; image forensics; Fuzzy theory;Forgery detection tools