摘要
在大型视觉多媒网络中,大量的干扰噪点坏数据对多媒体网络的稳定运行造成威胁,对此提出一种基于线性叠加细节捕捉的大型视觉多媒体网络的坏数据高效检测方法,采用Canny边缘检测函数,得到多媒体网络的换数据图像噪点边缘分割的不变矩阈值,采用经验模式设定进行坏数据检测,使用特征向量的最近邻匹配法可以找出音视频数据的潜在的匹配对,采用标准的基于数学形态学的分割方法得到最小割标准,实现检测算法改进,仿真结果表明,该算法能有效提高对坏数据检测的性能,具有较强的抗干扰性能和鲁棒性.
In the large visual multimedia network threat interference noise,a lot of bad data and stable operation of the multimedia network,resulting in multimedia audio and video signal errors in visual and the sense of hearing,the performance is not good.A bad data of large visual multimedia network of linear superposition detail capture efficient detection method is proposed based on edge detection function,using Canny,get the multimedia network data exchange noise edge invariant moment threshold image segmentation,using empirical mode setting for bad data detection,feature vectors using nearest neighbor matching method can identify audio and video data on the potential of matching,using the standard segmentation method based on mathematical morphology to get the minimum cut criteria,realization of improved detection algorithm,the simulation results show that,the algorithm can effectively improve the bad data detection performance,strong anti interference performance and robustness.
出处
《微电子学与计算机》
CSCD
北大核心
2015年第5期143-146,共4页
Microelectronics & Computer
基金
国家自然科学基金项目(61302124)
江苏理工学院校青年科研基金项目(KYY13027)
江苏理工学院教学改革项目(11610311415)
关键词
多媒体
计算机视觉
检测算法
multimedia
computer vision
detection algorithm
