：为解决现有视频监控系统中目标检测算法无法应付复杂的室外环境且计算量和存储量较大等问题，将像素从RGB 空间转换到YUV

空间建立基于码本的背景模型，并单独对每个码字中的亮度分量进行高斯建模，提取运动目标的轮廓后，用连通区域算法对图像进行形态

学处理。典型测试序列和ROC 数据的对比实验结果证明该算法是高效和实用的，且易于在DSP 或FPGA 等嵌入式系统上实时实现。-】In order to solve the problems that the existing motion detection algorithm in surveillance system can not work well in complex outdoor

scene, and needs too much computation and memory, this paper proposes a moving objects detection algorithm based on improved codebook model.

Pixels are converted from RGB space to YUV space to build the Codebook Model(CBM), and then the luminance component of each codeword is

modeled by Gaussian model. The image is morphological processed by connected components algorithm. A test with the typical video sequences and

the analysis of ROC data prove that the algorithm is effective and practical, and it can easily be implemented in embedded system such as DSP and

FPGA.