一种多特征融合的运动目标检测算法

A multi-feature fusion moving target detection algorithm

针对传统的混合高斯背景模型目标检测算法在复杂背景干扰和阴影条件下无法准确检测出目标的问题,提出一种多特征融合的运动目标检测算法.将包含上下文信息的局部二值模式(context local binary patterns,CLBP)纹理特征和HSV颜色特征的色调信息相结合,利用CLBP直方图向量和局部色度向量与高斯背景模型进行匹配实现运动目标检测.结果表明,该算法在满足实时性的前提下,对受阴影、目标遮挡和图像抖动等干扰时的目标检测准确性较高.

The traditional Gaussian mixture model target detection algorithm can not detect the problem accurately under complex background interference and shadow conditions.This paper proposes a multi-feature fusion moving target detection algorithm.It combines the local binary pattern texture feature which contains context information with the hue information of the HSV color feature.LBP histogram vector and local hue vector are used to match Gaussian background model to achieve moving target detection.The results show that the proposed algorithm has higher accuracy in the case of shadow,target occlusion and image jitter under the premise of satisfying real-time.