基于多支持区域局部亮度序的图像伪造检测

doi:10.11772/j.issn.1001-9081.2019020306

计算机应用 ›› 2019, Vol. 39 ›› Issue (9): 2707-2711.DOI: 10.11772/j.issn.1001-9081.2019020306

• 虚拟现实与多媒体计算 • 上一篇下一篇

基于多支持区域局部亮度序的图像伪造检测

颜普^1,2, 苏亮亮^1,2, 邵慧², 吴东升²

1. 智能建筑与建筑节能安徽省重点实验室(安徽建筑大学), 合肥 230022;
2. 安徽建筑大学电子与信息工程学院, 合肥 230601

收稿日期:2019-02-25 修回日期:2019-05-04 发布日期:2019-09-10 出版日期:2019-09-10
通讯作者: 颜普
作者简介:颜普(1986-),男,安徽亳州人,讲师,博士,CCF会员,主要研究方向:计算机视觉、模式识别;苏亮亮(1986-),男,安徽安庆人,讲师,博士,CCF会员,主要研究方向:视频图像处理、模式识别;邵慧(1979-),女,安徽长丰人,副教授,博士,主要研究方向:机器学习、图像处理;吴东升(1966-),男,安徽枞阳人,教授,博士,主要研究方向:电磁场理论、数据挖掘。
基金资助:
国家自然科学基金资助项目（61672032）；安徽省自然科学基金资助项目（1908085QF281）；安徽建筑大学博士科研启动基金资助项目（2017QD13，2015QD07）。

Image forgery detection based on local intensity order and multi-support region

YAN Pu^1,2, SU Liangliang^1,2, SHAO Hui², WU Dongsheng²

1. Anhui Provincial Key Laboratory of Intelligent Building and Building Energy Conservation(Anhui Jianzhu University), Hefei Anhui 230022, China;
2. College of Electronic and Information Engineering, Anhui Jianzhu University, Hefei Anhui 230601, China

Received:2019-02-25 Revised:2019-05-04 Online:2019-09-10 Published:2019-09-10
Supported by:
This work is partially supported by the National Natural Science Foundation of China (61672032), the Natural Science Foundation of Anhui Province (1908085QF281), the Doctoral Scientific Research Foundation of Anhui Jianzhu University (2017QD13, 2015QD07).

摘要/Abstract

摘要：

图像伪造检测是目前数字图像处理领域中的一个研究热点，其中复制-粘贴是最常用的伪造手段。由于伪造区域在粘贴前会被进行一定的尺度、旋转、JPEG压缩、添加噪声等操作，这使得检测伪造区域具有一定的挑战性。针对图像复制-粘贴伪造技术，提出一种基于多支持区域局部亮度序模式（LIOP）的图像伪造检测算法。首先，利用最大稳定极值区域（MSER）算法提取具有仿射不变性的区域作为支持区域；其次，利用非抽样Contourlet变换得到不同尺度、不同分辨率和不同方向的多个支持区域；然后，在每个支持区域上提取同时具有旋转不变性和单调亮度不变性的LIOP描述子，并利用双向距离比值法实现特征初匹配；接着，采用空间聚类将匹配的特征进行归类，进而用随机抽样一致性（RANSAC）算法对每个归类进行几何变换参数估计；最后，使用必要的后处理等操作来检测出伪造区域。实验表明，提出的算法具有较高的伪造检测精度与可信度。

关键词: 图像伪造, 复制-粘贴检测, 多支持区域, 非抽样Contourlet变换, 局部亮度序模式

Abstract:

Image forgery detection is currently one of the research focuses of digital image processing, and copy-move forgery is the most frequently used techniques in it. The forgery region is subjected to the operations of scale, rotation, JPEG compression, adding noise and so on before the image moved in, thus detecting the forgery becomes hard. Aimming at the image copy-move forgery technology, an image forgery detection algorithm based on Local Intensity Order Pattern (LIOP) and multiple support regions was proposed. Firstly, the affine invariant regions were detected as support regions by Maximally Stable Extremal Region (MSER) algorithm. Secondly, multiple support regions of different scales, resolutions and directions were obtained by NonSubsampled Contourlet Transform (NSCT). Thirdly, the LIOP descriptors invariant to monotonic intensity change and image rotation were extracted on each support region, and the initial feature matching was implemented via bidirectional distance ratio method. Fourthly, spatial clustering was used to classify the matching features, and geometric transformation parameters were estimated for each cluster by using RANdom SAmple Consensus (RANSAC) algorithm. Finally, the essential operations like post-processing were performed to detect the forgery regions. The experimental results show that the proposed algorithm has higher forgery detection accuracy and reliability.

Key words: image forgery, copy-move detection, multi-support region, Nonsubsampled Contourlet Transform (NSCT), Local Intensity Order Pattern (LIOP)

中图分类号:

TP391.41

颜普, 苏亮亮, 邵慧, 吴东升. 基于多支持区域局部亮度序的图像伪造检测[J]. 计算机应用, 2019, 39(9): 2707-2711.

YAN Pu, SU Liangliang, SHAO Hui, WU Dongsheng. Image forgery detection based on local intensity order and multi-support region[J]. Journal of Computer Applications, 2019, 39(9): 2707-2711.

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基于多支持区域局部亮度序的图像伪造检测

Image forgery detection based on local intensity order and multi-support region

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