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Pixel and Edge Based Illuminant Color Estimation for Image Forgery Detection

机译:基于像素和边缘的光源色彩估计,用于图像伪造检测

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Images are one of the powerful media for communication. Image security is a main issue in the fields that using digital images. By the development of high resolution cameras, personal computers and photo-editing software's, the manipulation of images is becoming common. This paper mainly focuses on common form of image manipulation such as image splicing. The process of analysis is done with the help of inconsistencies in illuminant color of images. Illumination inconsistencies detection is a powerful way for image forgery detection. Inconsistency detection among different images can be identified with the help of pixel and edge based illuminant color estimation on image regions. From these illuminant estimators, extract shape and color features, which is then provided to a classifier for making decision. Classification using SVM and its performance is evaluated using distinct testing process. The main contribution of this method is, how illuminant color estimation on various constraints can be exploited as a forgery detection method and how these are provided for decision-making with minimal user interaction.
机译:图像是进行交流的强大媒体之一。在使用数字图像的领域,图像安全是一个主要问题。随着高分辨率照相机,个人计算机和照片编辑软件的发展,图像的操纵正变得越来越普遍。本文主要关注图像处理的常见形式,例如图像拼接。分析过程是在图像的光源颜色不一致的情况下完成的。照明不一致性检测是图像伪造检测的有力方法。可以借助图像区域上基于像素和边缘的光源颜色估计来识别不同图像之间的不一致检测。从这些光源估计器中提取形状和颜色特征,然后将其提供给分类器以进行决策。使用不同的测试过程评估使用SVM进行的分类及其性能。该方法的主要贡献在于,如何将各种约束条件下的发光颜色估计用作伪造检测方法,以及如何将这些约束条件用于在最少的用户交互作用下进行决策。

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