基于自适应分割和特征提取的图像伪造定位方法

T. Parameswaran, S. Kaushik, Yogesh
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引用次数: 0

摘要

确认和确定计算机图像的质量,批准其实质和识别伪造的要求至关重要。因此,在高级图像验证中值得注意的空间是复制移动欺诈识别(CMFD)。自适应分割技术是一种确定重复移动模仿位置的方法。利用本文提出的通用分割计算技术,将图像自适应地分割为无覆盖和不均匀的碎片。然后,从每个正方形中提取组件关注点作为块确定,然后将正方形选择相互协调,以识别标记的组件焦点,指示涉嫌欺诈或伪造的位置。为了更准确地定位伪造区域,采用了仿区提取算法,该算法用小超像素代替元素焦点作为高光块,从而将具有比例阴影替代的相邻块合并到组件正方形中以获得连接的区域。最后,合并位置,并应用形态学处理构造经典伪造区域。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Methodology to Locate Image Falsification Using Adaptive Segmentation and Feature Extraction
The requirement for confirming and unwavering quality of computerized images, approving their substance and identifying fabrications is vital. Consequently, noteworthy space in advanced picture verification is Copy-move fraud recognition (CMFD). The Adaptive division technique is one to decide the duplicate move imitation location. The image is adaptively divided into non-covering and uneven fragments using the proposed versatile division computation technique. The component attentions are then extracted as piece determinations from apiece square, and the square choices are then harmonized with one another to identify the labelled component focuses, indicating the alleged fraud or falsification locations. To locate the falsification areas all the more accurately, the imitation district extraction algorithmic is utilized that substitutes the element focuses with little super pixels as highlight pieces so consolidates the neighboring blocks that have proportional shading alternatives into the component squares to get the joined locales. Finally, merge the localities and apply the morphological process to construct the classic faked areas.
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