阈值
计算机科学
局部二进制模式
帧(网络)
人工智能
特征(语言学)
商
模式识别(心理学)
二进制数
点(几何)
帧间
相关性
特征提取
计算机视觉
剩余框架
相关系数
参考坐标系
图像(数学)
数学
电信
直方图
机器学习
哲学
算术
纯数学
语言学
几何学
作者
Zhenzhen Zhang,Jianjun Hou,Qinglong Ma,Zhaohong Li
摘要
ABSTRACT Frame insertion and deletion are common inter‐frame forgery in digital videos. In this paper, an efficient method based on quotients of correlation coefficients between local binary patterns (LBPs) coded frames is proposed. This method is composed of two parts: feature extraction and abnormal point detection. In the feature extraction, each frame of a video is coded by LBP. Then, quotients of correlation coefficients among sequential LBP‐coded frames are calculated. In the abnormal point detection, insertion and deletion localization is achieved by using Tchebyshev inequality twice followed by abnormal points detection based on decision‐thresholding. Experimental results show that our method has high detection accuracy and low computational complexity. Copyright © 2014 John Wiley & Sons, Ltd.
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