复杂背景下的颜色分离背景差分目标检测方法

An Improved Color Separation Method for Object Detection in Complex Background

针对复杂背景下运动目标检测失检率高的问题,提出了用于复杂背景目标检测改进的基于RGB颜色分离的背景差分目标检测方法。主要是对RGB三通道图像独立进行背景差分运算,阈值二值化后合并三通道前景图像,得到完整前景目标图像;再利用检测的边缘对前景图像进行修正,消除光照变化带来的噪声;RGB三通道使用自适应权值的递推算法进行背景更新。最后采用实验室采集的图像序列进行了仿真实验,结果表明,该方法在复杂场景下有效识别颜色差异,避免了灰度值相近而造成的目标缺失,提高了检测精确性。

An improved background subtraction algorithm based on color separation method is introduced to solve the problem of high rate of missing detection of moving object in complex background.First,the current and background color images are individually divided into three images according to RGB channels.Then the background subtraction is made,and the object with threshold in every channel is segmented.After that,three result images are combined to obtain a completed foreground image.Edge subtraction result is used to fix the foreground image so that the noise brought by light is removed.At the same time,the background image from each channel is updated adaptively,in real time and individually.The results show that this method can effectively detect the difference of color which cannot be found by tranditional method because of similar grayscale in complex background.